{"as_of":"2026-08-08T01:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1ed115b094c775b2dac0f8ee41ccb985acae76c3b000ec7cb560564b80a245de","coverage":[{"denominator":27,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":27,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:41:34.481054Z","state":"measured"},{"denominator":27,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":27,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2506.07234/citation-record","integrity":"/paper/2506.07234/integrity","json":"/paper/2506.07234/citation-record.json","paper":"/paper/2506.07234"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:41:34.913265Z","title":"Pneumonia classification using deep learning from chest x-ray images during covid-19.Cognitive Computation, pages 1–13, 2021","venue":null,"work_id":"f4811d77-3906-4281-b488-52eab297669f","year":2021},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.378480Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:7cca5ac143f125d56d70eaf31ddcb242b95568b4da83969e6a3e96f79669fa71","observation_id":"7bbb23d0-8b99-45b5-be51-c65d434d1476","resolution":{"observed_at":"2026-08-07T05:41:34.917356Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.901238Z","title":"Deep learning algorithm for covid-19 classification using chest x-ray images.Computational and Mathematical Methods in Medicine, 2021(1):9269173, 2021","venue":null,"work_id":"fc803c82-dd11-4566-8b87-4db15515be08","year":2021},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.383167Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:f0454abfa63c1570121bd821833f16980a36a34d86101823d025e260b2a00534","observation_id":"d915bcf3-ee1b-4b89-8d4f-4a7dc4894fc8","resolution":{"observed_at":"2026-08-07T05:41:34.905284Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.889515Z","title":"Analysis of covid-19 data using advanced machine learning models","venue":null,"work_id":"8bdd43e4-109b-4864-99cb-15807cea70d9","year":2022},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.387285Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:f0e03077d53277c376838b5ee44cc9a584384c93d7b8080ab62223c64bf6dcd3","observation_id":"6f0e36e8-0b7d-49cb-b072-efc2bc70bbef","resolution":{"observed_at":"2026-08-07T05:41:34.893361Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.877384Z","title":"A machine learning-based framework for diagnosis of covid-19 from chest x-ray images.Interdisciplinary Sciences: Computational Life Sciences, 13:103–117, 2021","venue":null,"work_id":"1c920f4e-fdbb-4321-b16e-ccaa1de96bf8","year":2021},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.391338Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:4f07af26860716c13e0debf160e6ca63902973eb61eda936e4f8bfe2600c901d","observation_id":"4a35df33-e646-41b9-9853-2c63ea56b743","resolution":{"observed_at":"2026-08-07T05:41:34.881609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.865563Z","title":"Covid detection from cxr scans using deep multi-layered cnn","venue":null,"work_id":"93dda3dc-45a7-4962-999d-a1c5c482637d","year":2020},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.395296Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:46bce75a9f4b0e6aab5e9cd16f982481714450942c4165683f0bf37b20487927","observation_id":"d660fd6a-f635-4e55-90bc-c8348e5983e9","resolution":{"observed_at":"2026-08-07T05:41:34.869584Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.853374Z","title":"Empowering covid-19 detection: Optimizing performance through fine-tuned efficientnet deep learning architecture.Computers in Biology and Medicine, 168:107789, 2024","venue":null,"work_id":"c662d07d-938f-4bc0-81ec-8ebd4def93ed","year":2024},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.399615Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:ca6978b0cbeff5acca7d86572c103d26c0c6642fea9b211800ae49d2013d08e4","observation_id":"eb35728e-9844-4e6d-8dc3-46f70155a1f0","resolution":{"observed_at":"2026-08-07T05:41:34.857486Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.841393Z","title":"Pre-trained xception model-based covid detection using cxr images","venue":null,"work_id":"7934ddd2-2fe5-442b-a8c7-da8b3f441eab","year":2022},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.404209Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:2491bda985d2b8e0737d0fb8b5a5935eeb5a30be6bb05fcb0d3d2cf6437dd97c","observation_id":"b0865719-64ea-46ea-b14a-6759c524c44f","resolution":{"observed_at":"2026-08-07T05:41:34.845304Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.828731Z","title":"Applications of machine learning algorithms to support covid-19 diagnosis using x-rays data information","venue":null,"work_id":"2071c331-79a4-4896-867d-ff4e62e3dc64","year":2024},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.408149Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:8a3fe1684d0433ede997d53410f0979d66b55818466746991608e54b498ef594","observation_id":"e6424b1b-8d24-459a-8cfe-e682cb21b010","resolution":{"observed_at":"2026-08-07T05:41:34.833428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.815708Z","title":"Covid-19 ct-images diagnosis and severity assessment using machine learning algorithm.Cluster Computing, 27(1):547–562, 2024","venue":null,"work_id":"62e0b3c4-5b2f-44ea-9a2b-3995cfc28f62","year":2024},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.412068Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:efcc428790aa9005dd0868faafc50ca9222b486866bc2db80bc737c59bfa34b9","observation_id":"e9d32274-f722-4faa-aab1-ecc2066e1e4f","resolution":{"observed_at":"2026-08-07T05:41:34.819710Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.803880Z","title":null,"venue":null,"work_id":"66f2c433-e0a8-49b6-82dc-ccc75949df05","year":2023},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.415846Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:67b38cd025de75f2f1b1671bb4ebe11082370e97d6679551d372df229c4a3634","observation_id":"1da4c2f0-1256-4300-8f03-a9b5f5abbd44","resolution":{"observed_at":"2026-08-07T05:41:34.807638Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.791680Z","title":"Efficient gan-based chest radiographs (cxr) augmentation to diagnose coronavirus disease pneumo- nia.International journal of medical sciences, 17(10):1439, 2020","venue":null,"work_id":"3bdf9416-e253-47fc-a8f8-15260d3157a4","year":2020},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.419698Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:4bb5d1c6f056b2d8500dae6a9eb79ff6d9d1c4ac36fa51f6cb462dbb738a38ac","observation_id":"0b6b1ee8-08eb-4c19-9900-111eaa66e21f","resolution":{"observed_at":"2026-08-07T05:41:34.795824Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.779672Z","title":"Unveil- ing covid-19 from chest x-ray with deep learning: a hurdles race with small data.International Journal of Environmental Research and Public Health, 17(18):6933, 2020","venue":null,"work_id":"355ff1b6-a72d-4e2c-b384-aff549c2791a","year":2020},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.423525Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:a80c75d20cc38166d83090e0963ed6dd9c8dc52d879b1176064c41e077af51fd","observation_id":"878e9980-14fa-432b-a7ef-76a27ed1c037","resolution":{"observed_at":"2026-08-07T05:41:34.783847Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.767863Z","title":"Rezaul Karim, Till Döhmen, Michael Cochez, Oya Beyan, Dietrich Rebholz-Schuhmann, and Stefan Decker","venue":null,"work_id":"1b9dfc07-b00c-4e62-ad7a-f7d4702968e1","year":2020},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.427290Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:954ace51239a94dd1672138bd38b78d1fe579345c1e77bcf15b72dc2eb5f69c9","observation_id":"8f31539c-e7ca-4887-8c4d-27a37988367e","resolution":{"observed_at":"2026-08-07T05:41:34.771806Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.755317Z","title":"Covid-net cxr-2: An enhanced deep convolutional neural network design for detection of covid-19 cases from chest x-ray images.Frontiers in Medicine, 9:861680, 2022","venue":null,"work_id":"05bf759c-f3d5-4558-91b7-b3b0008abfd9","year":2022},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.431350Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:da635424b97c920d7c36449abccb55598da0a686e1e0bf65c69e7d184ac215c8","observation_id":"d857d337-6bb0-468b-afc0-f58f22d84a50","resolution":{"observed_at":"2026-08-07T05:41:34.759712Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.742490Z","title":"Weakly labeled data augmentation for deep learning: a study on covid-19 detection in chest x-rays.Diagnostics, 10(6):358, 2020","venue":null,"work_id":"305a91cb-f565-4e76-b5e8-a8d224b49bcb","year":2020},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.435361Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:1c28e107f0a068fd85317276c38dee8d5a6931786fffee785d07709af8d5ac4a","observation_id":"409f8ddb-a127-45e3-90d1-d3d7c78b6a16","resolution":{"observed_at":"2026-08-07T05:41:34.746856Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.730377Z","title":"Alderson, Lucas S","venue":null,"work_id":"00b7c31e-130c-4a06-883f-4b77e668041d","year":2020},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.439192Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:89127a8997246e6bfba2b88ac289905dcf0905b9d945d49397555a51223facb0","observation_id":"c93f6284-aa44-4532-a8e1-78d9a3c78c7d","resolution":{"observed_at":"2026-08-07T05:41:34.734249Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.718032Z","title":"Deep gru-cnn model for covid-19 detection from chest x-rays data.IEEE Access, 10:35094–35105, 2022","venue":null,"work_id":"18caa4a4-c70f-4498-9215-e3b66c635a41","year":2022},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.442914Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:18314e9dc8830604c0c9969975a7a0dbf05f7146326257afbc29c547d753239d","observation_id":"ac2d10c5-3a40-4237-9a15-915948606717","resolution":{"observed_at":"2026-08-07T05:41:34.722175Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.705353Z","title":"Svd-clahe boosting and balanced loss function for covid-19 detection from an imbalanced chest x-ray dataset.Computers in Biology and Medicine, 150:106092, 2022","venue":null,"work_id":"b682fb75-2f2e-479d-a2a7-635575a30a24","year":2022},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.446718Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:8db85f9e5bb25d09a10bcba64382f24544ceccfc82172abef55e56c1d0d35400","observation_id":"f5e726a6-426b-406b-a824-a321bcd0a2cf","resolution":{"observed_at":"2026-08-07T05:41:34.709566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.691847Z","title":"Covid-19 detection from xray and ct scans using transfer learning","venue":null,"work_id":"9fbdd23a-579f-4bd1-83aa-fc998cd063a9","year":2021},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.450487Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:0178c866e31b8c321c02df56438bffbd48813a6860a757fb1af9309cab9dabc2","observation_id":"69a7f75f-bf4b-4077-b2da-5452a54043e9","resolution":{"observed_at":"2026-08-07T05:41:34.696491Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.678230Z","title":"A comparative study of deep learning networks for covid-19 recognition in chest x-ray images","venue":null,"work_id":"4991af69-bb41-4bc8-9a09-5d00bbe01c01","year":2021},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.454250Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:3e78b4946e27413efdd09acda41c040f3fb4ab889d9640e07253c9ec773aaa07","observation_id":"a08972c2-2f4c-45c4-9218-8c7d3161b511","resolution":{"observed_at":"2026-08-07T05:41:34.682628Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.665087Z","title":"Classification of covid-19 from chest x-ray images using deep convolutional neural network","venue":null,"work_id":"ffd43135-92c7-4d07-ae90-41920315770d","year":2020},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.458117Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:246cfdc4c24cd69a0a51756f9fbc0031725f634322520435bec9f3ee5a24919a","observation_id":"2effa3b2-96ba-42b1-b054-8c1f3ebceade","resolution":{"observed_at":"2026-08-07T05:41:34.669639Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.652597Z","title":"Goldgof, Rahul Paul, Dmitry B","venue":null,"work_id":"8b7fdca3-2baa-4f7a-a431-6abf5d445757","year":2021},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.462238Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:608467958b83ab66a7841d281af83b6dcfd6c8409e2e4f6c15843c0c6e5abb0c","observation_id":"e742b8b5-3336-4de0-bb78-14c35febd674","resolution":{"observed_at":"2026-08-07T05:41:34.656532Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.639708Z","title":"Covid-19 detection through x-ray chest images","venue":null,"work_id":"3759c8c7-3f5c-4b10-b7ae-396d31be8dfe","year":2020},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.465950Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:daaed87db794dca7693c3cba73ea3109280bfc2d427f144cdf57d5bec3634fe7","observation_id":"4f948241-9d66-4bd5-9a95-5beb28f6c3a8","resolution":{"observed_at":"2026-08-07T05:41:34.643844Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.625971Z","title":"Lime-enabled investigation of convolutional neural network performances in covid-19 chest x-ray detection","venue":null,"work_id":"acaf7a22-3364-4213-8f7d-d91b9f0598b9","year":2021},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.469734Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:8c0bf8c6e1020b146c3ee74706f4104f0d1d99e81ba123ee9f1c62eb4ae4c229","observation_id":"4fe33c01-1c3f-44f0-b42e-c552711b3a01","resolution":{"observed_at":"2026-08-07T05:41:34.631077Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T05:41:34.473484Z","title":"Smote: synthetic minority over-sampling technique.Journal of artificial intelligence research, 16:321–357, 2002","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.473484Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:64faf106fbf46db5e80cc69caff44c96fd535030cc0848675cacf7f177bf042b","observation_id":"7faf017b-74fc-4130-b513-a356a0fbee4c","resolution":{"observed_at":"2026-08-07T05:41:34.473484Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:41:34.477169Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.477169Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:558d748f3ab25fcfd7f3f1cf48f11141894a6a24a53647a0b801e5f84a9c8a66","observation_id":"962c6b32-76a8-4d75-86f8-12c24470cc46","resolution":{"observed_at":"2026-08-07T05:41:34.477169Z","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":"2026-08-07T05:41:34.508255Z","title":"why should i trust you?","venue":null,"work_id":"91200143-ceb2-4760-b74b-0c9d553ccf9f","year":2016},"citing_paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:34.481054Z"},"links":{"citing_paper":"/paper/2506.07234"},"observation_digest":"sha256:5ac7cd6d6c5986aebee85f3a9bff234e65d35a6cc91a935a18b8c12aed13e0eb","observation_id":"071f949a-3549-4987-8ce4-485124b27782","resolution":{"observed_at":"2026-08-07T05:41:34.513714Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.07234","last_updated":"2025-06-08T17:38:14Z","latest_version":1,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-07T05:46:19.777234Z","submitted_at":"2025-06-08T17:38:14Z","title":"A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI"},"reference_resolution":{"displayed":27,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":0,"verified_fuzzy":24},"total_outbound_references":27},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2506.07234."}