{"as_of":"2026-08-16T22:08:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:abc9ae9bae786596fc5b837cf38d5dcdf9cadc67b529c9f968034428e57d2067","coverage":[{"denominator":18,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":18,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T15:07:39.492029Z","state":"measured"},{"denominator":18,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":18,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+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/2507.16668/citation-record","integrity":"/paper/2507.16668/integrity","json":"/paper/2507.16668/citation-record.json","paper":"/paper/2507.16668"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2023.10105","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T15:07:39.863452Z","title":"Forecasting energy power consumption using federated learning in edge computing devices,","venue":null,"work_id":"31144f19-774f-4814-b0bb-0ff09908cc16","year":2024},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:37.695598Z"},"links":{"citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:722e33d8ed3cee1eb474efe6aa3688dac49a33d7d34f308cb906bd4d5753a958","observation_id":"1587cfd3-35ae-479c-98e2-273ecf0c47ae","resolution":{"observed_at":"2026-08-06T15:07:39.893990Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T15:07:42.531948Z","title":"Comparative analysis of machine learning techniques for non-intrusive load monitoring,","venue":null,"work_id":"5e598444-05bd-41da-afb6-b88fe680a786","year":2024},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:37.802237Z"},"links":{"citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:1c1e3f103089261769505d424da0ad3ce3c9a1e02e022c31703aa26da278fefb","observation_id":"2ac44241-c61e-489b-a812-3149c8f291c0","resolution":{"observed_at":"2026-08-06T15:07:42.654495Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T15:07:42.373090Z","title":"Focca: Fog– cloud continuum architecture for data imputation and load balancing in smart grids,","venue":null,"work_id":"70ab4817-8ca3-4036-a14e-6a4adec75cab","year":2025},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:38.123344Z"},"links":{"citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:b050c0545c310cf2ad5200df451da380a3244847051a841352159386961becab","observation_id":"9fc7fab6-aa19-46d2-a66a-398b89f11435","resolution":{"observed_at":"2026-08-06T15:07:42.467196Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T15:07:42.220793Z","title":"Hierarchical scheduling mechanisms in multi-level fog computing,","venue":null,"work_id":"53ddfa59-d3e2-4d4d-8f9e-e9d7a6ff5c88","year":2022},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:38.288248Z"},"links":{"citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:613a36b95358319261dca6a7e8db00d305d6b278150a80bd907de4b33ca2c5ce","observation_id":"b2ff8895-8d91-419c-8c9a-19201c33e116","resolution":{"observed_at":"2026-08-06T15:07:42.279881Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T15:07:42.061153Z","title":"Sla-based task offloading for energy consumption constrained workflows in fog computing,","venue":null,"work_id":"9b32a6ef-4a6e-4701-921b-1971c2c6d70a","year":2024},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:38.475055Z"},"links":{"citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:c3f375c1298e121e8e3ec9c081281b8146b7f46b47d466435a0b152d585572eb","observation_id":"9e0bb1d1-cf28-4ec3-8231-e2061a8b53d0","resolution":{"observed_at":"2026-08-06T15:07:42.156066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T15:07:41.877206Z","title":"On incen- tivizing resource allocation and task offloading for cooperative edge computing,","venue":null,"work_id":"d5520925-8155-4a8f-9762-836b95d144e6","year":2024},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:38.538588Z"},"links":{"citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:2c62824e18c9e9d872d51fc7910d7625c902dd7cd2b48e9d7a36fac0dc7e9c63","observation_id":"f82b2b10-8788-40dd-8bcd-5a33f7700eb3","resolution":{"observed_at":"2026-08-06T15:07:41.969853Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T15:07:41.685063Z","title":"A survey on smart grid technologies and applications,","venue":null,"work_id":"d33787f2-4037-46b7-92d9-075cc24f3311","year":2020},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:38.636535Z"},"links":{"citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:2577c08a925cc1d307ea2a19487d293470aa6c42ccd0c25ab5552f816cff31c6","observation_id":"0bab586c-c54f-4bcb-8f0f-3ee0aee244df","resolution":{"observed_at":"2026-08-06T15:07:41.779725Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T15:07:41.484213Z","title":"A self-stabilizing and auto-provisioning orchestration for microservices in edge-cloud con- tinuum,","venue":null,"work_id":"70446603-3952-4c54-a8c1-48d7f2deb53d","year":2024},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:38.697307Z"},"links":{"citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:008b99bcef0dca7d0761896a2c7067b227b79e99b85dbc7120ebf5847f87f9f2","observation_id":"5177d4d4-51dd-4e25-bf11-6531ebdccee1","resolution":{"observed_at":"2026-08-06T15:07:41.581042Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T15:07:41.254218Z","title":"Fog computing model to orchestrate the consumption and production of energy in mi- crogrids,","venue":null,"work_id":"e3ae7087-736e-4a8b-806e-69cdd6a5addd","year":2019},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:38.798231Z"},"links":{"citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:eaf796b9b453404e797d22147f51a3a4b3f3da16683147697a61dead6037e9b6","observation_id":"7b9cc8b2-1fe1-48d3-b098-93e2ad3eda03","resolution":{"observed_at":"2026-08-06T15:07:41.349625Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.07012","last_updated":"2024-10-21T14:53:11Z","snapshot_observed_at":"2026-08-16T14:11:24.080314Z","submitted_at":"2024-03-09T10:01:49Z","title":"A PID-Controlled Non-Negative Tensor Factorization Model for Analyzing Missing Data in NILM","version":2},"cited_work":{"arxiv_id":"2403.07012","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.07012","snapshot_observed_at":"2026-08-06T15:07:39.597908Z","title":"A PID-Controlled Non-Negative Tensor Factorization Model for Analyzing Missing Data in NILM","venue":"cs.LG","work_id":"2b73bc87-3a26-4439-a397-7c8a4517a243","year":2024},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:38.887495Z"},"links":{"cited_paper":"/paper/2403.07012","citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:62f4bc3a77f189a59576834c342e1c84f862dcc37ced5dc22ca5388bbeb016cf","observation_id":"c7590ee8-4401-4037-aa04-22f2e301df75","resolution":{"observed_at":"2026-08-06T15:07:39.662096Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T15:07:41.055461Z","title":"Energy-aware resource management in fog computing for iot applications: A review, taxonomy, and future directions,","venue":null,"work_id":"ef024ff4-94b1-4360-8c0d-3cb421a879c8","year":2024},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:38.965312Z"},"links":{"citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:ea03997734940852e7835ea6233de19ead8e3c11d4e30aec06f3571ae1443a21","observation_id":"c88b12a6-f58b-4664-a5ad-0e78db544c94","resolution":{"observed_at":"2026-08-06T15:07:41.151002Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T15:07:40.905756Z","title":"Fog computing for smart grid systems in the 5g environment: Chal- 12 lenges and solutions,","venue":null,"work_id":"3a500d42-9c27-4392-92c8-e8027c87f1f3","year":2019},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:39.074988Z"},"links":{"citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:a511c5255d183991d2c9cb4cd1b254d449057d69f67d669940e0bb0606f699ee","observation_id":"ffefb41e-263f-47d8-ad3f-ac8bc8b12ff7","resolution":{"observed_at":"2026-08-06T15:07:40.983082Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T15:07:40.735130Z","title":"Lbatsm: Load- balancing aware task selection and migration ap- proach in fog computing environment,","venue":null,"work_id":"a2238ac7-b2bd-451c-b52c-627b403b8526","year":2024},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:39.081504Z"},"links":{"citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:572e296d704b518ca42ce548ad08f544af2c873e6b3b632edf52fb0a3383cecb","observation_id":"ee268756-3990-4060-aa56-65c36da92f37","resolution":{"observed_at":"2026-08-06T15:07:40.819729Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T15:07:40.549313Z","title":"Fdpr: A novel fog data prediction and recovery using efficient dl in iot net- works,","venue":null,"work_id":"c9a4f491-df2f-4444-bee1-dd03b6b99a81","year":2023},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:39.148431Z"},"links":{"citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:2d7a0f1cb5752003dcb9d5d0ad5a9fcf72eb5fffaab6c8c8cafc0d9f0c27a489","observation_id":"de5bb98a-c280-4540-a699-54e89f37c3f1","resolution":{"observed_at":"2026-08-06T15:07:40.669088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T15:07:40.353387Z","title":"An integrated deep learning and edge computing framework for intelli- gent energy management in iot-based smart cities,","venue":null,"work_id":"5699d330-a103-4902-94ae-fe2b01f5e6f7","year":2023},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:39.251814Z"},"links":{"citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:fb20de1f68f931593159e0e2191dd97e3958ede327b167be0b0f23f285ca4846","observation_id":"046347a6-e6fc-4965-a973-222a7d08b2f7","resolution":{"observed_at":"2026-08-06T15:07:40.448201Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T15:07:40.160788Z","title":"Optimal energy- efficient resource allocation and fault tolerance scheme for task offloading in iot-fog computing net- works,","venue":null,"work_id":"7a448785-a04d-414f-b4b1-8a518b73ca02","year":2024},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:39.325050Z"},"links":{"citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:bde749b6921ba03968a280d6e5cba54d63df891e96553cecda3e66a16ab811ae","observation_id":"f1ecb762-2b26-4a18-bd0f-bde276da4425","resolution":{"observed_at":"2026-08-06T15:07:40.273451Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T15:07:39.981524Z","title":"Workload allocation in iot-fog-cloud ar- chitecture using a multi-objective genetic algo- rithm,","venue":null,"work_id":"674be283-aafe-4625-952c-dd5097bab1d9","year":2020},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:39.409268Z"},"links":{"citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:7712fe3ac186d6e069d7a22e7a3da990d1f8f72b3ca6b76d64913945081feea3","observation_id":"11c15c36-ace8-4124-9f35-75a8aa7a8ed1","resolution":{"observed_at":"2026-08-06T15:07:40.083112Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.12523","last_updated":"2025-05-18T19:17:03Z","snapshot_observed_at":"2026-08-16T08:51:11.045078Z","submitted_at":"2025-05-18T19:17:03Z","title":"Energy-Aware Deep Learning on Resource-Constrained Hardware","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.12523","snapshot_observed_at":"2026-08-06T15:07:39.492029Z","title":"Energy-aware deep learning on resource- constrained hardware,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T15:07:39.492029Z"},"links":{"cited_paper":"/paper/2505.12523","citing_paper":"/paper/2507.16668"},"observation_digest":"sha256:2f57621f81f3074a9570eaa7a60dee12ff633c18ba8f5a7551c6cf60a11a705c","observation_id":"ba2cd8c3-5d4b-4c83-a64b-04dacc1cd2fb","resolution":{"observed_at":"2026-08-06T15:07:39.492029Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.16668","last_updated":"2025-07-22T15:01:16Z","latest_version":1,"primary_category":"cs.DC","snapshot_observed_at":"2026-08-14T09:48:38.043771Z","submitted_at":"2025-07-22T15:01:16Z","title":"FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture"},"reference_resolution":{"displayed":18,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":1,"verified_exact":1,"verified_fuzzy":15},"total_outbound_references":18},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2507.16668."}