{"as_of":"2026-08-10T12:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:94fb25e7d8c13a3471f6eaea078a338a462898b5c37b36acccdd6b58efd29000","coverage":[{"denominator":56,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":56,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-08T17:47:16.694416Z","state":"measured"},{"denominator":56,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":56,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2605.05034/citation-record","integrity":"/paper/2605.05034/integrity","json":"/paper/2605.05034/citation-record.json","paper":"/paper/2605.05034"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In: 2024 27th International Conference on Computer and Information Technology (ICCIT)","venue":null,"work_id":"019da56c-4559-4154-b346-7b99f92fa077","year":2024},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:3d2fbadbb8147aa2e12bff09582ddc6da0ee4bc756261c9ec7e5c00465c10797","observation_id":"e11ccfa5-bfbb-44cb-b872-e167201c2d0d","resolution":{"observed_at":"2026-05-26T06:41:52.029154Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In: 2024 6th International Conference on Sustainable Technologies for Industry 5.0 (STI)","venue":null,"work_id":"c24274d8-1aba-42f1-9723-0bea4518eda6","year":2024},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:0e4608842a238a2bc8b39edbd77c597d0d6722e2f04c100b435daadefb0695ce","observation_id":"8c0c9fda-9ec1-456d-9da2-01a3d8b6173b","resolution":{"observed_at":"2026-05-26T06:41:52.039661Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"6847cad4-4be5-4fcf-8eaf-36653ff2b76a","year":2025},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:056d8c77f403534f76350bdeecea708b6c5ffe70b35d81b95856986d56faa472","observation_id":"2dd72811-e254-4371-b9c0-401991f2923d","resolution":{"observed_at":"2026-05-26T06:41:52.043323Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"IEEE Access10, 68868–68884 (2022) 2","venue":null,"work_id":"08f23a73-795e-49cd-8df3-01bcbd85d82c","year":2022},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:494fe68eba948ee368e12bcb336bf95bf69313ba190b856c7fd3dda371745d35","observation_id":"c1ce75db-f2d0-45a3-908a-d663290a33be","resolution":{"observed_at":"2026-05-26T06:41:52.025933Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In: 2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","venue":null,"work_id":"4bcba869-b858-4b13-a4af-7452436f29f7","year":2024},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:68da2c0479f575061e7a6f8c0296eb09dcc8e85b960ef851fa00fcc0de6b62ee","observation_id":"a8b501eb-0506-4243-9531-8c1cfde9ffcd","resolution":{"observed_at":"2026-05-26T06:41:52.036118Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Natural Language Processing Journal7, 100079 (2024) 2","venue":null,"work_id":"bdd74910-ab84-43cb-a016-4e9f2259312d","year":2024},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:09541b060446589585b805d9920dfd4976cb90509d76854643bb1a4f04cd8a05","observation_id":"0eb392f4-9809-4807-a536-fd22f14953e4","resolution":{"observed_at":"2026-05-26T06:41:52.032639Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In: Proceedings of the 2023 6th International Conference on Machine Vision and Applications","venue":null,"work_id":"676faf0b-c723-46f2-a118-1a1dd0003724","year":2023},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:8beeba5dd488e21458d597dd25e23740cf54e38985440f2e86228a17b6c1d578","observation_id":"3ad70289-5ded-477a-b64a-4060ccb5eaf4","resolution":{"observed_at":"2026-05-26T06:41:52.022838Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Clinical Immunology (Orlando, Fla.)243, 109108–109108 (2022) 2","venue":null,"work_id":"4d004da4-86c9-4b70-86e1-dd659b5c4778","year":2022},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:4c438029586613b60ea258ef76a8e26b7ceb395aefd4e0f425a82946ad89b609","observation_id":"aa9c51a4-2790-418a-97f8-a01e3ea241e5","resolution":{"observed_at":"2026-05-26T06:41:52.009591Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"bead00aa-5d8b-4397-8dde-230194e36aa4","year":2023},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:516e95819fc35555f83702cc50af163931f2d6f536397a6349e241ab38b41de6","observation_id":"1b5188b0-bd7a-4bdc-b706-bd59eca778f5","resolution":{"observed_at":"2026-05-26T06:41:52.012661Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"31923b75-3e79-471a-9f72-1ebc76811e95","year":2022},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:d2ceda97a6cf2debbce59dce6c19900554661e46ce87995a4be4aefebf771ccb","observation_id":"4cd5dcd5-03a8-4a2f-8d9a-1667584aa425","resolution":{"observed_at":"2026-05-26T06:41:52.000388Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"144845d0-3593-4b63-b78f-eb358ad2ccf4","year":2025},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:9d56b90212e11377ad9aabc3edced54a28e054e0107dccbb24ecdfdbee585322","observation_id":"be6ee5b9-8c69-4ad7-9e5a-025bda86a51b","resolution":{"observed_at":"2026-05-26T06:41:51.985580Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"IEEE Access10, 92597–92632 (2022) 2","venue":null,"work_id":"7e7a7143-8b56-4321-a9a4-d7c256d51b19","year":2022},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:8dad8aff59d208a8d83e8e4dd5eb622f6c9a3157ea3c33160423c6a2a0dbcb79","observation_id":"969b2692-b9b6-4f67-886c-d1ae2e38e1f8","resolution":{"observed_at":"2026-05-26T06:41:51.979963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In: 2023 26th International Con- ference on Computer and Information Technology (ICCIT)","venue":null,"work_id":"fd960176-3097-4430-bcfe-51e04cfe3a35","year":2023},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:d7c2d22986b863db4dd896406e50ec346e00b352edc2419228224b6e8bb249d7","observation_id":"64fb87d8-197d-4723-a601-ecfa2e8bd58f","resolution":{"observed_at":"2026-05-26T06:41:51.982666Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Neural Networks161(2023) 2, 3, 4, 5, 6","venue":null,"work_id":"f3a28ec2-b0f2-4a55-9c45-caf7f98aeadc","year":2023},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:eb35af3d94868f57a9caed3eedd6e5919b86eb761fdd15874314e98f7bc57071","observation_id":"6d7601a9-c422-4b0a-9111-cba3f6a875d3","resolution":{"observed_at":"2026-05-26T06:41:51.991056Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In: Farkaš, I., Masulli, P., Wermter, S","venue":null,"work_id":"01bf79d4-6f52-4930-97c3-f71f586c06d6","year":null},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:e1279a9c55f9454a0043e66b692af4bc3120952dad9d1fed079e39d008502e7b","observation_id":"6b2ab431-2dbd-4002-9514-237a4fab5c66","resolution":{"observed_at":"2026-05-26T06:41:51.997430Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"c279d5ef-32f3-4e3b-86ec-dc41c0ef5fa2","year":2020},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:77c47577a492b23eefff052056eba90de23de2708b3b8c9c167dc0d3be402248","observation_id":"820df478-61fa-4d7c-874e-5ca00d9009cf","resolution":{"observed_at":"2026-05-26T06:41:51.971525Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Medical image analysis 75, 102305 (2021) 2 13","venue":null,"work_id":"a504c0bf-5e89-402f-b719-92cb763924e1","year":2021},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:508f8323fb50d629068e148dabaf9ddf3b8b68f6f621aff0ec7ec736aadf5326","observation_id":"a12ae204-7c29-4d76-aa32-cda3ba7961a5","resolution":{"observed_at":"2026-05-26T06:41:51.959620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Journal of biomedical informatics p","venue":null,"work_id":"41264cea-d6bd-4197-a520-300afd646e87","year":2023},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:02ab2975c6bf7e5a97c7fae7d566ca5fae8aa356a5133e6213903cb82a9449b5","observation_id":"13694e43-b914-4379-a2c7-73e983962103","resolution":{"observed_at":"2026-05-26T06:41:51.974237Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Pattern Recognition (2023) 2","venue":null,"work_id":"b68e9193-2e8b-4e73-9971-f826388fb08a","year":2023},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:80208e12667923f612f8324d11ac04047d7171bfde26bc1aefe62dba3a3718a7","observation_id":"520e6cae-f5a8-457c-a00e-ffeedda4c13e","resolution":{"observed_at":"2026-05-26T06:41:51.988481Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Frontiers in Medicine11(2024) 2","venue":null,"work_id":"67cd2391-5583-4af3-b788-629d9f56af56","year":2024},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:74152113ed833018d912847b13a1565e94f6bb40b3b471880c6ac36e0979ad50","observation_id":"124773bb-2ab3-4ee9-b4fd-a791fc7e622e","resolution":{"observed_at":"2026-05-26T06:41:52.019580Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"45b5c1c1-1a1f-4788-954c-7f7b5db39d2e","year":2025},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:746c0c541d3959cc31c47d46e9d8e85bf874e95a7194cb610e9dd496c9f846ce","observation_id":"6b04b478-5b75-4e63-9899-07f4a0dc40de","resolution":{"observed_at":"2026-05-26T06:41:51.899881Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.15459","last_updated":"2022-11-21T13:30:34Z","snapshot_observed_at":"2026-08-09T10:16:13.258018Z","submitted_at":"2022-11-21T13:30:34Z","title":"Classification of Human Monkeypox Disease Using Deep Learning Models and Attention Mechanisms","version":1},"cited_work":{"arxiv_id":"2211.15459","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2211.15459","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"ArXivabs/2211.15459(2022) 2","venue":null,"work_id":"3ce56942-1059-4201-a7fa-2600ffa7324b","year":2022},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"cited_paper":"/paper/2211.15459","citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:b1c936a21445f914321594a254046b962f7a2094450602e86f3554d558c2a14e","observation_id":"51d12619-4d0a-4ff2-8610-71637847e2d0","resolution":{"observed_at":"2026-05-11T17:16:06.519150Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Journal of King Saud University - Com- puter and Information Sciences35(7), 101641 (2023) 2","venue":null,"work_id":"5e2420c4-6752-4716-935e-1a52d78d73ea","year":2023},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:9520b4511f7ae505e3d4bc792a5aa6d25f20e09d68667cf0dc26c4321ef3c98a","observation_id":"93a40660-242f-4566-b666-6d3965071425","resolution":{"observed_at":"2026-05-26T06:41:51.935025Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"8c30813d-02d9-441f-ab9f-e62f9b8c3aec","year":2015},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:904e4410589083f017f95ea9ab9cae0bdaadd886832280da80cb48dd41ad56e6","observation_id":"93b09dca-6004-4419-8644-a680bf0f4b5c","resolution":{"observed_at":"2026-05-26T06:41:51.937858Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"f134b07d-a86d-4f00-a4c2-ad6cb2460d05","year":2018},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:1936d4e76fea118548b9a53fa44280d17657f38a26b997783f5c2707615aaafc","observation_id":"a5d28755-6a8f-4343-b2d8-7f2ec48b4f47","resolution":{"observed_at":"2026-05-26T06:41:51.965484Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Journal of Artificial Intelligence and Metaheuristics (2023) 2","venue":null,"work_id":"1bfd5629-da32-4b42-a816-95925a772173","year":2023},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:b483e96434fdd6d50ed7a7e1052409c261859ef994e693ff7518372c20de02c9","observation_id":"9901ee9a-f73d-46fc-9ad2-09977481fb05","resolution":{"observed_at":"2026-05-26T06:41:51.885905Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In: 2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","venue":null,"work_id":"335835cc-5eb6-48fe-abb7-7a0f2039249c","year":2024},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:885f4b6ee9c775084adb61a2ff2f97a9b0a7b91e44a39ef2c460d6d9a53bbcc4","observation_id":"f38a8c30-08c8-4e85-8be9-d6224c863b74","resolution":{"observed_at":"2026-05-26T06:41:51.888544Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"IEEE Journal of Biomedical and Health Informat- ics27, 17–28 (2022) 2","venue":null,"work_id":"a3528a91-3d71-4560-805b-3fac70aeb907","year":2022},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:52f597519210deeafc93ff458f87db3637aba8577a4d24c391de2b031b8afdd4","observation_id":"5a22c020-b538-453b-88e1-ec405a1f8126","resolution":{"observed_at":"2026-05-26T06:41:51.928949Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In: 2023 International Joint Conference on Neural Networks (IJCNN)","venue":null,"work_id":"07d7adb4-1bb9-4272-9fd6-14a3be9c4f72","year":2023},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:19fef642038a52255e03f7467a6053fb33f313e6a786dec72cadac668845e082","observation_id":"e2f4180a-102b-4459-957b-7ad6cbf80ec9","resolution":{"observed_at":"2026-05-26T06:41:51.891448Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In: 25th International Conference on Computer and Infor- mation Technology (ICCIT)","venue":null,"work_id":"a01d4ff8-0775-4479-ab27-49b6d24a3633","year":2022},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:2c8350ca174d04c9ea60c875ccc68a8c5bb6e7322d2687cb462c865c9d201876","observation_id":"5c50a2c4-6303-4328-9a30-64e97d29fd52","resolution":{"observed_at":"2026-05-26T06:41:51.940913Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In: Proceedings of the First Workshop on Bangla Language Processing (BLP-2023)","venue":null,"work_id":"f9cd8c6f-0874-49a2-ba39-4794cd20c7b2","year":2023},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:7e39e6385515fdb2c525be98f7e442c8b8742faee77afa20c31625ff4d168746","observation_id":"77c303c3-2162-4878-9753-5898bfafa547","resolution":{"observed_at":"2026-05-26T06:41:51.922423Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In: Findings of the Association for Computational Linguistics: EMNLP 2023","venue":null,"work_id":"7f74f5fb-ec91-4e26-8dcf-9cd06b097dfe","year":2023},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:10c397c9038c647338ffe12d70097ce613f5e6a116a473e24ef3c94944ab3676","observation_id":"e8a467c7-435b-4fa1-87ce-de50a370da3f","resolution":{"observed_at":"2026-05-26T06:41:51.897132Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Journal of Innovative Image Processing (2025) 2","venue":null,"work_id":"01c38151-e988-4a58-8fd6-0552839829f1","year":2025},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:6e28a1c015008e6727dba604c342660badc8be59803f6383022c819cad9e7d21","observation_id":"8a6e6a79-1b19-4b26-ba6c-1524f2dad3db","resolution":{"observed_at":"2026-05-26T06:41:51.894301Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"IEEE Access12, 32819–32829 (2024) 2","venue":null,"work_id":"0e24efce-91f2-452a-9fc1-cbbcab9b8c3f","year":2024},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:ca10c356fc4072046602fb5f6739fbd15ad2c33bd3482df8ef83636418f07f71","observation_id":"be813a7d-84ab-4b9c-ac29-1a4b32cdea90","resolution":{"observed_at":"2026-05-26T06:41:51.994428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"IEEE Transactions on Geoscience and Remote Sensing57, 2290–2304 (2019) 2","venue":null,"work_id":"0fcf7e7f-c8c1-478f-98f4-04d9f391593e","year":2019},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:c559601e4992545a44ac55ead440b9d22fa1ac77c2b1ca5fbd928e41376d08b2","observation_id":"c73c87c5-ce1f-426a-8bdc-0a4b25aadb26","resolution":{"observed_at":"2026-05-26T06:41:52.016360Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In: Proceedings of the Conference on Empirical Methods in Natural Language Processing","venue":null,"work_id":"c1eff7d8-26ba-4fbc-9002-c32754646576","year":2023},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:bff0161e41254023fa41e0a1daf634c24079929b2630eae9607cf5e5737d017d","observation_id":"c7d7dc7a-1b08-42ba-a638-1130e2699060","resolution":{"observed_at":"2026-05-26T06:41:51.883331Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Morbidity and Mortality Weekly Report72, 68–72 (2023) 2","venue":null,"work_id":"7207718d-b9e5-4d32-bce7-6d82b1e82fc3","year":2018},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:475a05bddfb0fbfd814100562c702f493e174e84ab6b727c100000a5e5acb41d","observation_id":"acf86dbe-5480-44e4-b49f-de0cd26c7d2f","resolution":{"observed_at":"2026-05-26T06:41:51.926111Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Lancet (London, England)401, 60–74 (2022) 1","venue":null,"work_id":"3c4c9668-5f56-4d27-a652-c97e3c50d717","year":2022},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:02ef9fb2e0942fc91aac2e2a0ccd870bc76d9b57e6a00ce2e07fc7ac8e4064ca","observation_id":"4293dc97-94dd-4c87-a06b-29593a5a76bf","resolution":{"observed_at":"2026-05-26T06:41:51.912916Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Cureus15(2023) 2","venue":null,"work_id":"3a5c65eb-32fe-45b8-94f8-ca55706eeeb7","year":2023},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:72fcbf97b9424946acb911c23b216d6193e6259ce2034c163c2a45ca43729495","observation_id":"1acc3b16-ee2f-43a3-90a6-ce2b974ca6ab","resolution":{"observed_at":"2026-05-26T06:41:51.931719Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"IEEE Transactions on Medical Imaging41(2022) 2","venue":null,"work_id":"f5f82c94-1412-4cae-a275-bd5bcd216298","year":2022},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:db8a57b29ec0554f6fe3df01d9926fa0d534fbfe93920929ab12711e5b77fb0e","observation_id":"0319fce2-f7de-4f78-baaf-5c53c416e7f5","resolution":{"observed_at":"2026-05-26T06:41:51.909780Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Medical Science Monitor : International Medical Journal of Experimental and Clinical Research28, e938203–1 – e938203–3 (2022) 2","venue":null,"work_id":"a0856484-3521-4c7e-b753-c57a7b0200d1","year":2022},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:21bfc578e5d662dacc29f5db2411b62c305f43630cc0d6c9e28fdd19e72ec023","observation_id":"e8e2ccfd-8c40-4a15-9321-be8bab74777f","resolution":{"observed_at":"2026-05-26T06:41:51.906451Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"GeroScience44(2022) 2","venue":null,"work_id":"dc8ab645-de6b-48cc-9cba-7e90aa9e5dde","year":2022},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:69b340fe09921e873221908ea68f0219c428bf4b63519c8b373b3fe17b367f3d","observation_id":"d75b27b4-ca9e-4b6b-b68d-26f0c2b807f7","resolution":{"observed_at":"2026-05-26T06:41:51.902527Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In: ICCV 2025 Workshop on Cultural Continuity of Artists (2025) 2","venue":null,"work_id":"388dba12-1de0-4494-9101-798f110105fa","year":2025},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:6e4ac38dfc057e539c4f994d13c3c718e521cb81ff6bbd3e8fc5aa7f88464b87","observation_id":"4f73ab64-c887-43cf-99b9-1aa32f77c4cc","resolution":{"observed_at":"2026-05-26T06:41:51.916340Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"1ba8e424-f58b-4ec8-aa9e-7bcaa879719b","year":2019},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:74b2bc58c653f19624823ad8bfccbf6be0092350a91807fbb07a003c35540bcf","observation_id":"749f56a8-3685-46ff-8c7e-68f3c9f157c4","resolution":{"observed_at":"2026-05-26T06:41:51.919480Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"histopatho- logical images (2024) 8","venue":null,"work_id":"c527fa08-e3a9-47cd-8e66-0716c460e704","year":2024},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:9e4322932134f052cc27b2d3a2d7902ecf3ac70bd4559d679b8aa59d8ef8796d","observation_id":"e40a5706-9513-4c2b-8854-05664087ed52","resolution":{"observed_at":"2026-05-26T06:41:51.946957Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Infection50, 1425–1430 (2022) 2","venue":null,"work_id":"8dd84d54-e692-48c4-b7cd-5fefa86776df","year":2022},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:7dc73d0597d864e2d4ab4d1c9b9e4b0b41a97cef92d77bbbf1dde7457b4b6fe3","observation_id":"dfba113d-747b-485f-b838-878103683c51","resolution":{"observed_at":"2026-05-26T06:41:51.956301Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"0c087238-411f-4e62-bdfe-096ba908d9f7","year":2015},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:352d785fd04bcbc5995dcd48818864863c7e9c23fc2f1526ac3c82106f9d8891","observation_id":"78c3732d-480a-4e44-87ad-a7c3a7e38128","resolution":{"observed_at":"2026-05-26T06:41:51.962532Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Pattern Recognition120, 108111 (2021) 2","venue":null,"work_id":"bb454f88-0a77-4db1-9583-c5254a7df666","year":2021},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:07dde3b5121fd829eccce0d5b4f5b830566d48cfb8f6008c3235b403d17fad30","observation_id":"278cb8e9-cb29-4d98-a9d5-965c077dca2f","resolution":{"observed_at":"2026-05-26T06:41:51.949957Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"37152c81-e455-425b-a3ff-d81b8d53bffa","year":2015},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:6d53bc390181c6573ee7d9721a6d302962202f647a8b23cda1ed0dd32b1cd601","observation_id":"a9e92499-e8b4-43f2-a008-04c2642aa8ee","resolution":{"observed_at":"2026-05-26T06:41:52.003740Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"1a0561ab-37aa-4db6-93df-83b9616f1429","year":2024},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:2ecaba00921294f880055593d923e0fda9a6a65e2b368212a211a0484f17f6a4","observation_id":"cde66dc9-fdcd-4bd1-9c87-ab005ea541b3","resolution":{"observed_at":"2026-05-26T06:41:52.006543Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"35d91e9e-f652-48c5-a78a-051c31803a50","year":2020},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:ed09c39c16b744259de3cbb04eafad232e7703fc98ad755771a2c3384f86f402","observation_id":"dce75e62-0fca-473c-9c9d-012951ea4020","resolution":{"observed_at":"2026-05-26T06:41:51.977309Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"ACM Computing Surveys 55, 1–40 (2022) 2","venue":null,"work_id":"d20270b4-a1c4-435a-a9a6-f899f49f313d","year":2022},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:9de0f2f80274d89ed1ee0d222e3c3d32ea12d7a95d59364bcceb9df77d9ccf95","observation_id":"8e165a33-8635-4696-a910-aed8decc6390","resolution":{"observed_at":"2026-05-26T06:41:51.968498Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.04623","last_updated":"2019-11-16T00:35:54Z","snapshot_observed_at":"2026-07-06T08:36:17.259270Z","submitted_at":"2019-11-12T00:44:10Z","title":"SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning","version":2},"cited_work":{"arxiv_id":"1911.04623","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1911.04623","snapshot_observed_at":"2026-07-01T08:55:34.861866Z","title":"Learning robust global representations by penalizing local predictive power","venue":null,"work_id":"03cca62a-24e7-4f0f-b580-192a267bbda0","year":1911},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"cited_paper":"/paper/1911.04623","citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:1e23f15001fbf47de2a0cc62a4b737fcb421a8a675c4598227fffeb057ff33bb","observation_id":"0d56aab7-f3e7-4c2e-872a-a6d9a0c482aa","resolution":{"observed_at":"2026-05-11T17:16:06.524470Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1904.05046","last_updated":"2020-03-29T16:47:41Z","snapshot_observed_at":"2026-08-09T18:33:44.158007Z","submitted_at":"2019-04-10T08:05:48Z","title":"Generalizing from a Few Examples: A Survey on Few-Shot Learning","version":3},"cited_work":{"arxiv_id":"1904.05046","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1904.05046","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"ArXivabs/1904.05046(2019) 2","venue":null,"work_id":"bc5d01c2-356b-48bf-953e-aa9739ea3c14","year":1904},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"cited_paper":"/paper/1904.05046","citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:a98f8ca8492e97904d78a06256cc48205469361616412020218e689db1a3627b","observation_id":"aea41971-33b6-401c-9861-718893fb029f","resolution":{"observed_at":"2026-05-11T17:16:06.533773Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In: 2021 Joint 10th International Confer- ence on Informatics, Electronics & Vision (ICIEV) and 2021 5th International Conference on Imaging, Vision & Pattern Recognition (icIVPR)","venue":null,"work_id":"99a0aca3-de7f-457a-b1b0-17ec5fd23abd","year":2021},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:c648abe4e0d62e5fe24463a66c2ea571f419b2c4b3a8b669be6a6ebeaae69090","observation_id":"79c527a7-92ea-4662-8905-944a52a2dfb1","resolution":{"observed_at":"2026-05-26T06:41:51.953241Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"IET Image Process.17, 3589–3598 (2023) 2 15","venue":null,"work_id":"5c6e4bd5-6798-457a-998a-17979a5588bc","year":2023},"citing_paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-08T17:47:16.694416Z"},"links":{"citing_paper":"/paper/2605.05034"},"observation_digest":"sha256:3e920f610805be8c6c3a28f192e396b75414f7a6c9d7e0fc6702f6357cd3b44b","observation_id":"fdec1f6f-aa55-4e6f-8f8a-45e619553824","resolution":{"observed_at":"2026-05-26T06:41:51.943862Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2605.05034","last_updated":"2026-05-06T15:28:21Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-02T19:59:25.862937Z","submitted_at":"2026-05-06T15:28:21Z","title":"Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors"},"reference_resolution":{"displayed":56,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":13,"verified_exact":2,"verified_fuzzy":40},"total_outbound_references":56},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2605.05034."}