{"as_of":"2026-08-09T01:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d378b8918d3f39c2b5efcf7b218fceb7c2d65d7f1795c76d21c83759d2ec49d4","coverage":[{"denominator":22,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":22,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:11:02.737280Z","state":"measured"},{"denominator":22,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":22,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2505.19740/citation-record","integrity":"/paper/2505.19740/integrity","json":"/paper/2505.19740/citation-record.json","paper":"/paper/2505.19740"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:11:05.497779Z","title":"Machine learning approaches for microorganism identification, virulence assessment, and antimicrobial susceptibility evaluation using dna sequencing methods: A systematic review","venue":null,"work_id":"57f9dd8a-ff62-4559-966f-18d1cf69a1ff","year":2024},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:01.588793Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:ffa05be27e04eef01001981a39eda56ebedcb568918cbd6a7b2994730ede8aba","observation_id":"e2ac06e6-40d8-4a4a-a2be-9deea760e13a","resolution":{"observed_at":"2026-08-07T14:11:05.560397Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:05.398115Z","title":"Emerging applications of machine learning in genomic medicine and healthcare","venue":null,"work_id":"e67c5f65-70db-4663-91ee-04e76f5dfe7a","year":2024},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:01.638287Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:2c8709a9234bf5c4caf0741fc5ba2d79a81d8ed82d480a689d63c80a0bca4c9c","observation_id":"72c19210-4011-4bd8-9c97-92b5195e1173","resolution":{"observed_at":"2026-08-07T14:11:05.428813Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:05.284559Z","title":"Detecting risk gene and pathogenic brain region in emci using a novel gerf algorithm based on brain imaging and genetic data","venue":null,"work_id":"51ee4767-ca23-463d-b11f-7c4d8cf90d0a","year":2021},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:01.696856Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:e9f712312d2aa0ed7846b6cc4748c6da3255f4cf4f6a03b6bcbc8aaf33837fe5","observation_id":"cac5ad0c-c05f-48ac-b87a-78922193f898","resolution":{"observed_at":"2026-08-07T14:11:05.345202Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:05.173937Z","title":"Research and implementation of cancer gene data classification based on deep learning","venue":null,"work_id":"ba4e6ca0-0407-441e-a4dd-d32293a83d26","year":2023},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:01.740286Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:8ce84db990dcbf0fdc1d422db4233e810b01dcc90f860e8a95fd59bcec5e43ee","observation_id":"91263bbb-1424-47fc-a547-4b2044a8d2f5","resolution":{"observed_at":"2026-08-07T14:11:05.226227Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:05.032634Z","title":"An ensemble technique using genetic algorithm and deep learning for the prediction of rice diseases","venue":null,"work_id":"0ce2e30c-c3e5-4799-a15f-05f150a4d305","year":2025},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:01.797989Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:274b5beee8b49b5734778508ee5dd1b48216fc56db2bce5e4c3c65a5ef059b01","observation_id":"64e86815-334b-4cbc-ab89-aacb35957cf5","resolution":{"observed_at":"2026-08-07T14:11:05.097854Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:04.812388Z","title":"Stimulation of the production of prostaglandin e2 by ethyl gallate, a natural phenolic compound richly contained in longan","venue":null,"work_id":"a4f8f014-3b63-4a6b-af6a-60376e6181b3","year":2018},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:01.861563Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:33bc723bd1fa8db244df49dde0a5ebad46e20c613c0e0321bdc2f192b0e89328","observation_id":"bde3da38-ca64-4dc4-b6e3-158390987fc5","resolution":{"observed_at":"2026-08-07T14:11:04.896612Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:04.706184Z","title":"Ellagic acid, a plant phenolic compound, activates cyclooxygenase-mediated prostaglandin production","venue":null,"work_id":"40e77d02-b269-48d2-9882-69756b022949","year":2019},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:01.900854Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:321cf7f1b2318872311c7c6fb952a4671a7ab916f318c21407f16ebf70a4e8ef","observation_id":"ba5e0005-17b3-4d8c-a028-f0930b4ae0bf","resolution":{"observed_at":"2026-08-07T14:11:04.742797Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:04.521165Z","title":"Mechanism for the reactivation of the peroxidase activity of human cyclooxygenases: investigation using phenol as a reducing cosubstrate","venue":null,"work_id":"628776d0-6f16-4ed8-a4a3-b7fca32d5807","year":2020},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:01.940772Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:67c356f63091d1c18c8e86780c00dbc67aa75e4cca00a5c03552a4711e232242","observation_id":"c7d19fb4-5bd3-41ad-9402-787d48e3e1b0","resolution":{"observed_at":"2026-08-07T14:11:04.612500Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:04.333821Z","title":"Machine learning in drug discovery: a review","venue":null,"work_id":"ae3be6f4-cefa-4d26-a223-a821e61c4b83","year":1947},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:01.980721Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:da0de5b4fc3d397bfade75c6e91edbf6dfd55cf80e8fb72546de17df9ea48ee3","observation_id":"b94793b2-88ad-4696-8d79-5cc1714acb3e","resolution":{"observed_at":"2026-08-07T14:11:04.435102Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:04.145519Z","title":"Supervised machine learning classifies inflammatory bowel disease patients by subtype using whole exome sequencing data","venue":null,"work_id":"9f7c11a3-84b7-4e7d-b5b0-9ee532191589","year":2023},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:02.023037Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:aaadf16d190f7b6d0680f6ac8bad37c595820202b904f9b14f763478f85f30ba","observation_id":"9c35d5c8-c399-431b-b892-a6847dbda48b","resolution":{"observed_at":"2026-08-07T14:11:04.235802Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.19647","last_updated":"2025-03-28T04:18:10Z","snapshot_observed_at":"2026-08-03T13:42:11.797439Z","submitted_at":"2024-05-30T02:59:49Z","title":"FTS: A Framework to Find a Faithful TimeSieve","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.19647","snapshot_observed_at":"2026-08-07T14:11:02.077244Z","title":"Fts: A framework to find a faithful timesieve","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:02.077244Z"},"links":{"cited_paper":"/paper/2405.19647","citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:eb32b36111a237c807e85b015c9e6f23dacf456f8c90acb2bb45ef1e25650aa7","observation_id":"d731ea7c-1bf9-4480-90d2-afac5a52e850","resolution":{"observed_at":"2026-08-07T14:11:02.077244Z","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":"2026-08-07T14:11:04.057754Z","title":"Invariant spatiotemporal representation learning for cross-patient seizure classification","venue":null,"work_id":"e82fe47a-f176-4a36-8394-d948b2ed1137","year":2024},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:02.120688Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:f53557b7589a49ca679755a838955f38d3f7afa29f612868ad2f2decacff1a20","observation_id":"40cbc777-1b3f-43ef-8592-1ad45b0a1d3a","resolution":{"observed_at":"2026-08-07T14:11:04.080682Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:03.983167Z","title":"Causal recommendation via machine unlearning with a few unbiased data","venue":null,"work_id":"00c4aa84-ef9a-4b72-95f5-6152228c36c7","year":2025},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:02.178559Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:4ca9536f0ec370f176716cd4e69fd7091616876d01783f90272afb5a7e725841","observation_id":"b9181035-5dce-4df3-a3a7-42eb3f512d28","resolution":{"observed_at":"2026-08-07T14:11:04.005400Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:03.877643Z","title":"Biodeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding rna classification","venue":null,"work_id":"0a43e9f9-e877-4a29-b1ec-ee09f09232a7","year":2024},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:02.237221Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:bdce272e190afbd36e78c42c7ea855a8ebca2ad8054b0f13767e86ee2f24480c","observation_id":"0f7c6642-9567-4e2e-8127-1864e80f523b","resolution":{"observed_at":"2026-08-07T14:11:03.916798Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:03.721405Z","title":"Machine learning-assisted surface- enhanced raman spectroscopy detection for environmental applications: a review","venue":null,"work_id":"8330b798-22a8-4528-9cd8-d4f07573b59c","year":2024},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:02.356821Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:0c7fb3d112a5a3b6ebb3388136367815e7f71d2b8d1340404e1b8ff0bf38db5f","observation_id":"51ce7d7c-643f-4802-855f-c388178df764","resolution":{"observed_at":"2026-08-07T14:11:03.790481Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:03.550557Z","title":"Harnessing deep learning for population genetic inference","venue":null,"work_id":"b9785cec-4586-4f35-95e9-16cd68a97fcf","year":2024},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:02.391455Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:865f8f9f407d1377f45b464d6a1e1e31007c9ce72becaf4c1cf420a47d31e5a2","observation_id":"31f82e65-38c1-40ed-aabc-9f756a319177","resolution":{"observed_at":"2026-08-07T14:11:03.644118Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:03.465458Z","title":"Deep learning techniques in cancer prediction using genomic profiles","venue":null,"work_id":"74c3fe58-5e19-4fa4-8468-f77ab5640758","year":2021},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:02.446212Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:a9686ce063167ede1c11deeea041c1c74ee26649071a87db6aa282c9fb22803d","observation_id":"50d15ead-91ef-4407-a4b4-a2dd8a81ca19","resolution":{"observed_at":"2026-08-07T14:11:03.480923Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:02.559498Z","title":"Machine learning for microbiologists","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:02.559498Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:aaaee9307476cae161c36eb0bd5f41f6724f61797f6472bfaaca30970a4e61f7","observation_id":"efabdb78-6cb4-4afa-91f5-c56b76ebbf38","resolution":{"observed_at":"2026-08-07T14:11:02.559498Z","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":"2026-08-07T14:11:03.275038Z","title":"Predicting icu admissions for hospitalized covid-19 patients with a factor graph-based model","venue":null,"work_id":"0a1c64e7-5a04-45f7-95b0-4005b85b0c09","year":2022},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:02.607043Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:d4c0146d66a4982d174e580df3992269e36d5da40526ad05c75b51dcec3c7e25","observation_id":"a936cb38-c3e8-4e3b-a395-71cfb0b0154c","resolution":{"observed_at":"2026-08-07T14:11:03.348386Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:03.100594Z","title":"Cm-net: Concentric mask based arbitrary- shaped text detection","venue":null,"work_id":"bc834cb8-79a5-4404-b952-d76c2845664d","year":2022},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:02.647340Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:0acaa3d6315d4c0b575a16030ce05bd6862d506c3ec901db86d930641f462ef3","observation_id":"10b5dbc1-0311-4775-86f1-fe56a2ee01b0","resolution":{"observed_at":"2026-08-07T14:11:03.201180Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.02801","last_updated":"2025-01-07T10:09:18Z","snapshot_observed_at":"2026-08-03T14:39:49.817854Z","submitted_at":"2024-12-03T20:04:32Z","title":"Optimization of Transformer heart disease prediction model based on particle swarm optimization algorithm","version":3},"cited_work":{"arxiv_id":"2412.02801","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.02801","snapshot_observed_at":"2026-08-07T14:11:02.832169Z","title":"Optimization of Transformer heart disease prediction model based on particle swarm optimization algorithm","venue":"cs.AI","work_id":"ad236faf-d457-4a44-b0ac-4cc6fbec96c0","year":2024},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:02.687875Z"},"links":{"cited_paper":"/paper/2412.02801","citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:ebed4c53203219fdabdd0a28aacdcbc1a5509cc55181a01a115ce04259d4062b","observation_id":"3386a8cb-f791-49b6-9016-3ca7c08a392e","resolution":{"observed_at":"2026-08-07T14:11:02.890410Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:02.947579Z","title":"Interpretable machine learning enhances disease prognosis: Applications on covid-19 and onward","venue":null,"work_id":"4af7e021-005e-42de-b9a9-f8a8613687cc","year":2024},"citing_paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:02.737280Z"},"links":{"citing_paper":"/paper/2505.19740"},"observation_digest":"sha256:b44a65128fcde5ed144fb1c5273398a356a6dd2f8d6c39e9513a204cefe482c1","observation_id":"c877b400-fd80-4d39-8115-f7480f6dda0a","resolution":{"observed_at":"2026-08-07T14:11:03.014137Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.19740","last_updated":"2025-05-26T09:23:09Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T14:05:00.612087Z","submitted_at":"2025-05-26T09:23:09Z","title":"Machine Learning Algorithm for Noise Reduction and Disease-Causing Gene Feature Extraction in Gene Sequencing Data"},"reference_resolution":{"displayed":22,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":2,"verified_exact":1,"verified_fuzzy":19},"total_outbound_references":22},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2505.19740."}