{"as_of":"2026-08-14T18:02:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:27e01880e7a403ae96b7c79a019597a9775ec7a17dadb68c86d8130e89edf8ca","coverage":[{"denominator":45,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":45,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T19:05:01.060562Z","state":"measured"},{"denominator":46,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":46,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-17T20:36:13.408128Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-17T20:40:15.089521Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"cited_work":{"arxiv_id":"2507.06644","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.06644","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ali Mohamad-Djafari.Inverse problems in vision and 3D tomography","venue":null,"work_id":"b8713353-f96b-4200-a6e2-9611e935d540","year":null},"citing_paper":{"arxiv_id":"2511.16520","last_updated":"2026-05-12T03:36:08Z","snapshot_observed_at":"2026-08-13T10:39:16.880376Z","submitted_at":"2025-11-20T16:35:57Z","title":"Saving Foundation Flow-Matching Priors for Inverse Problems","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-17T20:36:13.408128Z"},"links":{"cited_paper":"/paper/2507.06644","citing_paper":"/paper/2511.16520"},"observation_digest":"sha256:3bf03eefa8dd7fa5c6f830ea943bd80bdb367c7700f6133434486754e94ef875","observation_id":"9278e2b3-d845-4669-a6a2-eb2eeee6810d","resolution":{"observed_at":"2026-05-17T20:40:15.092175Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2507.06644/citation-record","integrity":"/paper/2507.06644/integrity","json":"/paper/2507.06644/citation-record.json","paper":"/paper/2507.06644"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1073/pnas.111083998","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Proceedings of the National Academy of Sciences of the United States of America 98(12), 6641–6645 (2001) https://doi.org/10.1073/pnas.111083998","venue":"Proceedings of the National Academy of Sciences","work_id":"175a2165-c6f2-4b6f-8244-ce61f8539f81","year":2001},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:57.490814Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:9e281229706099e156194e3539b930dde422fcaa9ef998f3a8865b2e1fb61083","observation_id":"69ca1491-2a20-48db-a098-48b2b35159f3","resolution":{"observed_at":"2026-08-06T19:05:02.228312Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T19:05:03.034967Z","title":"Nature Materials 8(4), 291–298 (2009) https://doi.org/10.1038/ nmat2400","venue":null,"work_id":"fc1a023c-00ce-469d-ad44-09384c2fb7eb","year":2009},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:57.623526Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:d0de822573b235151d1b7abd966c0657614be660599d6bb6b6157bc9c7cee05a","observation_id":"bbffe287-d9a3-4b6d-8c6f-061e9a41c83d","resolution":{"observed_at":"2026-08-06T19:05:03.045813Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1107/s1600576722002886","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Journal of Applied Crystallography 55(3), 621–625 (2022) https://doi","venue":"Journal of Applied Crystallography","work_id":"ca903ffd-489c-423c-ac59-15c2b03e9558","year":2022},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:57.663111Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:9c9ae2f77d531eeca9652704d5108e6758a7069d6e602648a07f4ec1f94c3687","observation_id":"e8a488f4-3450-49f5-aaba-4fb636dc3360","resolution":{"observed_at":"2026-08-06T19:05:02.198432Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41467-021-25625-0","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Nature Communications 12(1), 5385 (2021) https://doi.org/10.1038/s41467-021-25625-0","venue":"Nature Communications","work_id":"2069aa17-8adb-436b-96e9-c281744ade9b","year":2021},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:57.827744Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:6cca3674324afd85ea6c7281aac671888e2daf2521f29e1e0be2f8dbe88da17a","observation_id":"80c6f156-1999-4103-b12e-2046d67c364d","resolution":{"observed_at":"2026-08-06T19:05:02.150707Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1103/physrevmaterials.4.013801","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":null,"venue":"Physical Review Materials","work_id":"684bf0b1-0a96-4c41-b664-ce48def48732","year":2020},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:57.995362Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:ee558c5c29587b3b4b745f88eb8b5d6287eb5037d8a539affd4c8e35682cbdeb","observation_id":"5dc5e2fd-46fa-4233-9b22-4edfcc2d3f9d","resolution":{"observed_at":"2026-08-06T19:05:02.098263Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1107/s1600576721003113","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Journal of Applied Crystallography 54, 797–802 (2021) https://doi.org/10.1107/S1600576721003113","venue":"Journal of Applied Crystallography","work_id":"1dc54e33-36d4-4874-9618-a51327e0ae28","year":2021},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:58.117872Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:cd0a4cfdbc2993c51c2fc0ec2da2d41e5bf9c0dbff70e015ff3678fadad0306a","observation_id":"2ddedca8-9098-410a-834f-18b8c4be323d","resolution":{"observed_at":"2026-08-06T19:05:02.071897Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T19:05:03.001119Z","title":"Nature Communications 4 (2013) https://doi.org/10.1038/ ncomms2661","venue":null,"work_id":"01dcc92f-310a-458e-a8dc-be5301a1ca37","year":2013},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:58.265904Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:129e30a302be2817a3043fc902125177d61774b0165bb1e50997762049a58f36","observation_id":"6f5b685f-e49f-44fb-a65a-d543f48d4c88","resolution":{"observed_at":"2026-08-06T19:05:03.005502Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1088/1367-2630/aaebc1","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":null,"venue":"New Journal of Physics","work_id":"220cc780-ea07-4b01-bca5-5c1743e59821","year":2018},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:58.443323Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:ae7b12dba606b5df34a2c474e0bbb481710154e9d5acc96b8fb223f8fb6cc959","observation_id":"6f41004f-0720-4905-97bc-2b8692a76c51","resolution":{"observed_at":"2026-08-06T19:05:02.047222Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.cattod.2018.12.020","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Catalysis Today 336, 169–173 (2019) https://doi.org/10.1016/j.cattod.2018.12.020","venue":"Catalysis Today","work_id":"744e589e-af2c-43c7-a479-2411b4b7f3f4","year":2019},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:58.631072Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:9834b2aba62c7cb8bd43d66923f810970e35c4db4ef9be1d502c8dd27b52b83b","observation_id":"ae035aaa-4ede-4582-bb0f-455d05aaba50","resolution":{"observed_at":"2026-08-06T19:05:02.012656Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T19:05:02.974737Z","title":"Nature Communications 13(1), 3003 (2022) https://doi.org/10.1038/ s41467-022-30592-1","venue":null,"work_id":"0ce553cf-3a9e-45ac-a9c5-0ac7523bffbd","year":2022},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:58.777138Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:05f2dba727e4a46028e884cd233b472a87979012c4f6b89879c485c5329c9125","observation_id":"ddf5c20b-6e6a-4c48-a911-25304aa55463","resolution":{"observed_at":"2026-08-06T19:05:02.981319Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41563-023-01528-x","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Nature Materials 22(6), 754–761 (2023) https://doi.org/10.1038/s41563-023-01528-x","venue":"Nature Materials","work_id":"aac35412-08e6-4a8c-a9c8-1e286d453497","year":2023},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:58.937348Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:997b0bf6021fffeb6c9472706f7e01179e1effcfe0bc800a0474069a38df6e9a","observation_id":"cf5bedb8-b0fb-436b-9dba-36a1e40921d1","resolution":{"observed_at":"2026-08-06T19:05:01.994216Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T19:05:02.929284Z","title":"ACS Nano 18, 13517–13527 (2024) https://doi.org/10.1021/ acsnano.3c11534","venue":null,"work_id":"ac4b9f57-f8b8-4c55-8eb8-13cd05d1238e","year":2024},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:59.091480Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:345586a39c9f6e83803f8ce1209722b97bb5d5ee8e34f8fc755ba4f6f4521970","observation_id":"0ab735b1-8985-4a96-93be-35bbba255518","resolution":{"observed_at":"2026-08-06T19:05:02.934000Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T19:05:02.907963Z","title":"Optik 35, 237–246 (1972)","venue":null,"work_id":"4d71e197-6485-4bb1-a4f0-14f7f634b6ce","year":1972},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:59.207036Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:a248aee268f95dc56779c7b7c9a15fadd9cd5598758dbefa7bc3e3102b740be4","observation_id":"aeba01d9-c988-4c40-a07e-a407e02b53bf","resolution":{"observed_at":"2026-08-06T19:05:02.918030Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:04:59.270236Z","title":null,"venue":null,"work_id":null,"year":1978},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:59.270236Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:ec10e74e605453a37764463858366e2fbaa08b0b1d40d090dd8804ef7a5bdea7","observation_id":"b19b4d4d-a135-4868-9f8c-b42e8554081a","resolution":{"observed_at":"2026-08-06T19:04:59.270236Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:05:02.872908Z","title":"Review of Scientific Instruments 78(1) (2007) https://doi.org/10.1063/ 1.2403783","venue":null,"work_id":"4d57f09b-6193-4136-ae37-ce5ab4a04dfe","year":2007},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:59.402518Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:21c775dc1c19d5f3f2041a9d009d250099fbf1e8a1a1a6ce1121832af5ecb1b6","observation_id":"3c51f1a5-a54b-460f-bc3b-8c018a1eaec8","resolution":{"observed_at":"2026-08-06T19:05:02.884612Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1107/s1600576720010985","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Journal of Applied Crystallography 53, 1404– 1413 (2020) https://doi.org/10.1107/S1600576720010985","venue":"Journal of Applied Crystallography","work_id":"36e75eab-d8b8-498d-9b83-3879291e6d89","year":2020},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:59.562820Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:9abdb3ade98e61520c1fc637288fbf6925160b8c4a8a475ab3f0ee0e3334156b","observation_id":"23485944-a7d0-4e6f-8c1c-462a2292ee06","resolution":{"observed_at":"2026-08-06T19:05:01.917360Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1107/s1600576723007720","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Journal of Applied Crystal- lography 56(5), 1528–1536 (2023) https://doi.org/10.1107/S1600576723007720 https://onlinelibrary.wiley.com/doi/pdf/10.1107/S1600576723007720 13","venue":"Journal of Applied Crystallography","work_id":"15c9e8b1-38ac-425f-b6f9-af474f8590a3","year":2023},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T19:04:59.893797Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:09bf0565780127223dc8bc133d9a52e2f54596fb2db21c9dd2b5490afef79f56","observation_id":"8412dd92-956f-435f-97b4-420b0e7ff27a","resolution":{"observed_at":"2026-08-06T19:05:01.851722Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T19:05:02.820533Z","title":null,"venue":null,"work_id":"0ea81fb8-ff08-488e-b55f-4ea02ff52fcf","year":2025},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.053235Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:e3e65c612ee129f902405ccc658d2c0ffbe239f384a638ced66fe4b6c67b5c9b","observation_id":"f01d1e51-52a5-4be8-b323-0afcf967c96b","resolution":{"observed_at":"2026-08-06T19:05:02.846854Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1088/1367-2630/ab61db","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"New Journal of Physics 22(1), 013021 (2020) https://doi.org/10.1088/1367-2630/ab61db","venue":"New Journal of Physics","work_id":"fbfae3ac-56b7-4a49-a04d-dd4e778fa557","year":2020},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.223402Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:dba6f9bcd6a91f2b965fb4b52b309dfda6daec30e135531d87083cb63357cacc","observation_id":"7ac9ae87-bbd7-438d-9ba1-d5f221798cf0","resolution":{"observed_at":"2026-08-06T19:05:01.828663Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1103/physrevb.82.165436","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":null,"venue":"Physical Review B","work_id":"23671012-2401-4471-b775-61e70f13958e","year":2010},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.386820Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:8746128adbfe87e92416c54a25e18c40ce43fed72cfa02cc8a538f1ebcedfea0","observation_id":"82821baf-b51c-4f05-b748-ba42b6caceab","resolution":{"observed_at":"2026-08-06T19:05:01.814278Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1103/physrevb.78.174110","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Physical Review B - Condensed Matter and Materials Physics 78 (2008) https://doi.org/10.1103/PhysRevB.78.174110","venue":"Physical Review B","work_id":"80fd08ef-4850-47a5-9671-f200de951b35","year":2008},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.513276Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:153b79206fb6b141cf7f304e9977bf021247baceea29fc1917b7153251b36017","observation_id":"dc7c7c2f-243a-4755-9218-a044c17c67e1","resolution":{"observed_at":"2026-08-06T19:05:01.759274Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41598-018-34525-1","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Scientific Reports 8(1) (2018) https: //doi.org/10.1038/s41598-018-34525-1","venue":"Scientific Reports","work_id":"a80e3979-77db-46f1-8174-345330b65a1e","year":2018},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.518225Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:b842163c5be2717d46b4cc46de68fb45cbc7b93740ec5b4acc5ea327ca6b4de2","observation_id":"66b14720-29df-4567-9530-1f8cf7bcef39","resolution":{"observed_at":"2026-08-06T19:05:01.716350Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1063/5.0014725","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Journal of Applied Physics 128(18) (2020) https://doi.org/10.1063/5.0014725","venue":"Journal of Applied Physics","work_id":"539dc0d2-b3cd-4067-9d2b-6b46aca62061","year":2020},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.522935Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:e65877f584aac200030363c580db2aa780da6f9b3688633dbaba55cfb6657067","observation_id":"78f2d2f9-5264-41a2-b14d-d77b59485504","resolution":{"observed_at":"2026-08-06T19:05:01.640728Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T19:05:02.749384Z","title":"IUCrJ 8(1), 12–21 (2021) https://doi.org/10.1107/ S2052252520013780","venue":null,"work_id":"8fcccddf-ff49-4016-b7e7-70378548ca3b","year":2021},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.528238Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:1c19d6df3f969bd67b3673cabb637d246b785fed1600505b45691bdd568d9d1d","observation_id":"b3f4a952-8449-464a-97e7-48fbd3402815","resolution":{"observed_at":"2026-08-06T19:05:02.786151Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41524-021-00644-z","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"npj Computational Materials 7(1) (2021) https: //doi.org/10.1038/s41524-021-00644-z","venue":"npj Computational Materials","work_id":"6e00fdd2-383e-4928-af01-e9ea61fda66b","year":2021},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.532890Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:e9d659b10d6e5022980d4a38d23d17126294b20b1e1a3edcee0307e06ac3049a","observation_id":"bb03e9ce-5c8d-40d7-aac4-f8d9925049a5","resolution":{"observed_at":"2026-08-06T19:05:01.587341Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41524-022-00803-w","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"npj Computational Materials 8(1) (2022) https://doi.org/10.1038/s41524-022-00803-w","venue":"npj Computational Materials","work_id":"2a681110-9e77-42b6-b4f2-f6890bb63430","year":2022},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.536865Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:161b5ed35cca751c8bd74ba8ab100589fbf373a8e5f974237264558f89fa48f8","observation_id":"a9b6b201-faad-4d1a-a6a3-2d3eea8c146e","resolution":{"observed_at":"2026-08-06T19:05:01.571653Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T19:05:02.713359Z","title":"npj Computational Materials 10 (2024) https://doi.org/10.1038/ s41524-024-01208-7","venue":null,"work_id":"69b14163-163a-4f87-b213-668347891eba","year":2024},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.541919Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:4d23269948c8b860483f2179760b1a34597a40244716b30f03d891759d17723c","observation_id":"a3b5a2ba-5458-4ad8-b6b5-5ed1dcd69b7b","resolution":{"observed_at":"2026-08-06T19:05:02.727482Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T19:05:02.681599Z","title":"npj Computational Materials 9 (2023) https://doi.org/10.1038/ s41524-023-01022-7","venue":null,"work_id":"c5e24729-29ca-42cb-a719-f578b44dccdd","year":2023},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.552951Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:aea31bac1bbd67692cc78f9823ebc3186573901c0bf6837eddad6875154798c7","observation_id":"511b5511-1439-4f3c-aaec-c338a204d2dc","resolution":{"observed_at":"2026-08-06T19:05:02.686255Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/s23052640","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":null,"venue":"Sensors","work_id":"922d2aac-0c48-44c5-adc7-9f8fb826beef","year":2023},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.562628Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:e5bf475a1547ffa3faf5f2602c8d5460914793806a31eec570d20698eba6e73e","observation_id":"c77d5ff7-b195-4b2d-be1e-0fae5259f227","resolution":{"observed_at":"2026-08-06T19:05:01.527455Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T19:05:02.615957Z","title":null,"venue":null,"work_id":"1277eea2-c3e1-484d-b034-1732100a7c09","year":2024},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.566858Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:c9b40e1406580023bfbff4299661b64d020f5b6d682acde8d91e2f9747b22803","observation_id":"b86e9cc0-2991-498b-a9ce-5cff79cc7098","resolution":{"observed_at":"2026-08-06T19:05:02.638230Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41524-021-00583-9","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"npj Computational Materials 7(1) (2021) https://doi.org/10.1038/s41524-021-00583-9","venue":"npj Computational Materials","work_id":"f30c1e15-b45b-4d61-a2bf-5508251277b2","year":2021},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.585124Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:5ceac00eaa7982612f862805deb3214de891a5f4ae79ad4089c8d4f9e4908552","observation_id":"2a08b415-348a-48fc-a59d-5f95a46abd8b","resolution":{"observed_at":"2026-08-06T19:05:01.505027Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T19:05:02.582615Z","title":"Jour- nal of Applied Crystallography 44(3), 635–640 (2011) https://doi.org/10.1107/ S0021889811009009","venue":null,"work_id":"ac5e8c4a-dd4b-4f47-ab73-7a81b4cf896e","year":2011},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.594154Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:2c6342cdf384c39f9928fa14fcbae206cd44dd6c97d89a25a1c0af8d8bf323b2","observation_id":"5f92f6c0-e905-43d1-973a-fa946797dc5f","resolution":{"observed_at":"2026-08-06T19:05:02.597598Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1107/s1600576724004163","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Journal of Applied Crystallography57(4), 966–974 (2024) https://doi.org/10.1107/S1600576724004163","venue":"Journal of Applied Crystallography","work_id":"5b5020a0-8803-4786-a0dc-eeea60ada198","year":2024},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.610858Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:e7ad5b070b2c8214daac719f58fbd2dc29ff557e4803ab0e67d49ac244dba0b8","observation_id":"af57e686-5a33-49d6-b9f1-108a6935c7e3","resolution":{"observed_at":"2026-08-06T19:05:01.429441Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1606.06650","last_updated":"2016-06-21T16:42:20Z","snapshot_observed_at":"2026-08-08T13:52:24.420776Z","submitted_at":"2016-06-21T16:42:20Z","title":"3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1606.06650","snapshot_observed_at":"2026-08-06T19:05:00.637261Z","title":"https: //arxiv.org/abs/1606.06650","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.637261Z"},"links":{"cited_paper":"/paper/1606.06650","citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:e3a1ae2525c4ade61240dc9342b6dc455c5f27ad0568d9ce8d7f025f2f4f8f1c","observation_id":"9f5881ca-a7da-45fb-a839-bfa90c31bc7c","resolution":{"observed_at":"2026-08-06T19:05:00.637261Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:05:02.514242Z","title":null,"venue":null,"work_id":"3e0390fb-10ed-4e0e-a3e7-0cb5ac4a6c3f","year":2017},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.664627Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:e3941a6b27512c3025e7120911f2823b93460980e44b6a51dc2b80bb4b6408b0","observation_id":"74098e33-c4be-4df4-8b16-a746f3240ae9","resolution":{"observed_at":"2026-08-06T19:05:02.550903Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T19:05:02.480298Z","title":"In: Proceedings of the 21st ACM SIGPLAN International Conference on Functional Programming, pp","venue":null,"work_id":"f84959b2-e49f-4883-bd00-89e47fd29f6f","year":2016},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.668873Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:ae801a35c07fbcb5932d768a17c715dbd1c82ddb80abb74fe497cf6f73ec92ad","observation_id":"75ced089-69b2-4924-af20-0cb3250bbe01","resolution":{"observed_at":"2026-08-06T19:05:02.495697Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T19:05:02.454205Z","title":null,"venue":null,"work_id":"88f5d400-5057-43e4-be79-c16eb7cdce68","year":2017},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.684783Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:df068940fce8175bdd73ab3d443eee174d74edef1855a25daf3af887070c3933","observation_id":"705f4db8-ae19-4d6e-8b76-6b31e2eb8869","resolution":{"observed_at":"2026-08-06T19:05:02.463189Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T19:05:02.404720Z","title":null,"venue":null,"work_id":"bb45aa50-905b-439a-ad26-da5a71fc3ee4","year":2012},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.705256Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:6ef33bdba824ff38c788cd0de710d8929a001e93966de633f5ececd5e5d8431a","observation_id":"0d49e3a8-f4a0-4599-8088-d5b87115aca1","resolution":{"observed_at":"2026-08-06T19:05:02.417170Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.15448","last_updated":"2024-03-18T03:01:53Z","snapshot_observed_at":"2026-08-13T00:52:17.397818Z","submitted_at":"2024-03-18T03:01:53Z","title":"What is Wrong with End-to-End Learning for Phase Retrieval?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.15448","snapshot_observed_at":"2026-08-06T19:05:00.709547Z","title":"https://arxiv.org/abs/2403.15448","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.709547Z"},"links":{"cited_paper":"/paper/2403.15448","citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:f2a5f256cc15592820d2e148d0be84e1abc66c3c1d6770c0466079ed6e95216c","observation_id":"d5a3761f-d86f-4fa2-90fd-298f7f39f301","resolution":{"observed_at":"2026-08-06T19:05:00.709547Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.15151/esrf-dc-2184066699","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"European Synchrotron Radiation Facility","venue":"European Synchrotron Radiation Facility","work_id":"8f7993c3-821f-49df-a88c-a43f8ac230ac","year":2025},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.713966Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:e0df1406322454ed71b7e5b99154373168fbbb013e20b3623eb0a51ba1f316c9","observation_id":"919836ff-9b97-4948-a75a-ab47a4b8c746","resolution":{"observed_at":"2026-08-06T19:05:01.384124Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.15151/esrf-dc-2014789918","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"European Synchrotron Radiation Facility","venue":"European Synchrotron Radiation Facility","work_id":"b8a2ab22-5cb1-468e-b054-99bfcf40e9ad","year":2025},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:00.719351Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:8b897bef53176226a408dad67fd83caae13f6f8239221e8a88bdea32bd4d29b0","observation_id":"7ea8bb77-9895-4756-a956-7d4161eda32f","resolution":{"observed_at":"2026-08-06T19:05:01.303823Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1103/physrevb.68.140101","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Physical Review B - Condensed Matter and Materials Physics 68 (2003) https://doi.org/10.1103/PhysRevB.68.140101","venue":"Physical review. B, Condensed matter","work_id":"73d0f003-11c1-4e45-a2d2-6e80d893fea2","year":2003},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:01.040857Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:5d7c303e23d0b0c05c5f8c4f0a734cdcdf84087dfb4fd93e02692dc1d655b164","observation_id":"7be9f95b-fab4-4fbb-a708-f473b0ddb7e8","resolution":{"observed_at":"2026-08-06T19:05:01.266784Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1364/josaa.7.000003","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":null,"venue":"Journal of the Optical Society of America A","work_id":"64421e19-ac44-4933-bfc2-655ccaf92667","year":1990},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:01.048888Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:31251bb7d0bf70d537df26e98c6a85ec7e4fccb7bda1bde5e6ef59363138cd1f","observation_id":"06b857c1-3878-440e-8b4d-14d17f5dde18","resolution":{"observed_at":"2026-08-06T19:05:01.224326Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T19:05:02.388525Z","title":"https://doi.org/10.5281/ zenodo.7656853","venue":null,"work_id":"649ea47a-cebb-4605-8067-6e72caedec38","year":null},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:01.053566Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:feefedaf35f98ac9d76651332ba1764e68a6c623698a4422e5f39dd552483948","observation_id":"834aac6d-d06f-457c-b38d-0aa7b62ee833","resolution":{"observed_at":"2026-08-06T19:05:02.393394Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41598-020-57561-2","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Scientific Reports 10 (2020) https://doi","venue":"Scientific Reports","work_id":"3b63822d-92d4-476e-abf1-72e19ca26cf8","year":2020},"citing_paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:01.060562Z"},"links":{"citing_paper":"/paper/2507.06644"},"observation_digest":"sha256:864b8ccab242c197527baffd01581094025d6a875b7b77e2b6c5821727cbcb75","observation_id":"af5fd6e5-5eed-42c8-9fe3-2b2d72ba5734","resolution":{"observed_at":"2026-08-06T19:05:01.882343Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.06644","last_updated":"2025-07-09T08:17:03Z","latest_version":1,"primary_category":"cond-mat.mtrl-sci","snapshot_observed_at":"2026-08-10T21:44:15.539888Z","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network"},"reference_resolution":{"displayed":45,"state_counts":{"malformed_identifier":10,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":8,"verified_exact":25,"verified_fuzzy":2},"total_outbound_references":45},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 1 inbound Pith citation observation for arXiv:2507.06644."}