{"as_of":"2026-08-08T14:55:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8dc13ec52596fdc7231e890b97709ddd176fc29c85ad2a897796c1300a512ad6","coverage":[{"denominator":19,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":19,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T17:41:04.850445Z","state":"measured"},{"denominator":19,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":19,"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/2509.00035/citation-record","integrity":"/paper/2509.00035/integrity","json":"/paper/2509.00035/citation-record.json","paper":"/paper/2509.00035"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:41:05.230276Z","title":"Wafer level stress: Enabling zero defect quality for automotive microcontrollers without package burn-in,","venue":null,"work_id":"abe8834e-d95a-49da-803b-6e390c690710","year":2020},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.760658Z"},"links":{"citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:8d67cd1e0e2fe671d79e68e1a3bf93d05bf97bce1f14f67763a6e3ddf40830ce","observation_id":"96d8e4ee-5a44-473b-abbc-5e45242da017","resolution":{"observed_at":"2026-08-05T17:41:05.235168Z","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":"2026-08-05T17:41:04.765599Z","title":"Xgboost: A scalable tree boosting system,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.765599Z"},"links":{"citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:64d7c0e77f2824a9c974df0322774096517742cbc156e76656db6e0bb6a23d09","observation_id":"c144cb4c-ead7-473d-9905-890a0f06a2bc","resolution":{"observed_at":"2026-08-05T17:41:04.765599Z","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":"2026-08-05T17:41:05.205446Z","title":"Catboost: unbiased boosting with categorical features,","venue":null,"work_id":"3046bc0c-2246-4154-8a88-7ec3bd1140b7","year":2018},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.770275Z"},"links":{"citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:81599bb672ec8daa00ceaf6d0decfbaf499a50739aacc550043cf6046c63adf6","observation_id":"7a3bf28f-26de-4779-a724-7aab85b6a8a4","resolution":{"observed_at":"2026-08-05T17:41:05.210253Z","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":"2026-08-05T17:41:05.190568Z","title":"Domain-specific machine learning based minimum operating voltage prediction using on-chip monitor data,","venue":null,"work_id":"165c1245-10a9-40ce-ad8f-69a1c70494b4","year":2023},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.775616Z"},"links":{"citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:6d1df88f54a3a40aed85239ac44ae6fa7f3699d025bc1a6f62ca6432f9898e6b","observation_id":"09a7e804-899a-46f8-96f7-ee03977608db","resolution":{"observed_at":"2026-08-05T17:41:05.195853Z","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":"2026-08-05T17:41:05.175689Z","title":"Deep Lattice Networks and Partial Monotonic Functions,","venue":null,"work_id":"727bf0ed-b78f-4b7e-939d-d425d5e73a69","year":2017},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.780165Z"},"links":{"citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:f6f5aa644a0f2e265f5f8307cc1eb7edc9d6228f5272284f8be929ee1efd385c","observation_id":"6eae4555-6d2b-44b4-a510-93c36f427c4b","resolution":{"observed_at":"2026-08-05T17:41:05.180316Z","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":"2026-08-05T17:41:05.161345Z","title":"Lattice regression,","venue":null,"work_id":"13aaa93d-45bc-4051-bc46-1bdd44960d3a","year":2009},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.784944Z"},"links":{"citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:f63fd8901a653efed6fd4d5bc7d547423138dec242b4d591c2581500e4193fe1","observation_id":"62281d0a-6372-4a10-9235-4d9e51b1167b","resolution":{"observed_at":"2026-08-05T17:41:05.166027Z","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":"2026-08-05T17:41:05.145538Z","title":"Silicon odometer: An on- chip reliability monitor for measuring frequency degradation of digital circuits,","venue":null,"work_id":"13bb7d5b-d66e-4a9d-a05c-321aeb99b6fc","year":2008},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.790678Z"},"links":{"citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:d726a514bbe99c4d915ab7ff0446bd0ccb2c881a9ac7738141076a1a72f94ac6","observation_id":"876dc2e8-ca93-4f06-97cb-71306583466c","resolution":{"observed_at":"2026-08-05T17:41:05.151173Z","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":"2026-08-05T17:41:05.129176Z","title":"An all-in-one silicon odometer for separately monitoring hci, bti, and tddb,","venue":null,"work_id":"231e8618-c4c1-4ca9-9948-4d730d8b19c3","year":2010},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.795011Z"},"links":{"citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:1222c9f2b295e68f656e3d983a40c176cc026ce4a8eb5505f22f934c849af503","observation_id":"476e1418-515e-40ec-9e9d-3e5cfee33bdd","resolution":{"observed_at":"2026-08-05T17:41:05.134005Z","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":"2026-08-05T17:41:05.114081Z","title":"An array-based odometer system for statistically significant circuit aging characterization,","venue":null,"work_id":"5baf826c-44b2-4769-99ce-2af4c6796648","year":2011},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.800514Z"},"links":{"citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:65f851bd3850b2f48ab250ac1ba950410a847d08f17d888cbe3c4fab53106def","observation_id":"cdeae65b-3913-4dc6-b9c7-617932f2239d","resolution":{"observed_at":"2026-08-05T17:41:05.118866Z","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":"2026-08-05T17:41:05.097361Z","title":"Reliable interval prediction of minimum operating voltage based on on-chip monitors via conformal- ized quantile regression,","venue":null,"work_id":"aacc450d-be40-40ba-90ba-b9f2660a10a0","year":2024},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.804769Z"},"links":{"citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:5b36a19605d7f8a6eb7fe2ec80a63fda8fa1935618249797f43c8fa0b4745ae8","observation_id":"46d7422f-f516-4e45-9623-7412aeb7d7d2","resolution":{"observed_at":"2026-08-05T17:41:05.102837Z","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":"2026-08-05T17:41:05.082224Z","title":"Data-efficient prediction of minimum operating voltage via inter- and intra-wafer variation alignment,","venue":null,"work_id":"6d18d942-2237-4db1-9139-07f081855de2","year":2025},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.809201Z"},"links":{"citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:e64d84c949497b02c8c0f19aa4c5d739bc10555cd57f55e7b37532153463f26e","observation_id":"b3057596-5494-4083-b51d-16511b12f494","resolution":{"observed_at":"2026-08-05T17:41:05.087355Z","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":"2026-08-05T17:41:05.066743Z","title":"Minimum operating voltage prediction in production test using accumulative learning,","venue":null,"work_id":"6ceca465-ce19-4203-9d60-9d4485a72fb2","year":2021},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.814267Z"},"links":{"citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:c8c849f92ec987a3b8c9ac0d307ae34da1a13441b6eb50c5d5236802b53a55fe","observation_id":"11187bf4-9d35-4ceb-850d-083c5916acfc","resolution":{"observed_at":"2026-08-05T17:41:05.072079Z","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":"2026-08-05T17:41:04.819915Z","title":null,"venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.819915Z"},"links":{"citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:f2a5b857190e425cc90fa719c563079c7b07f081139836f5014c4ac710e1232d","observation_id":"50bf4f8f-fb93-4078-9568-c3a9ad40e6f9","resolution":{"observed_at":"2026-08-05T17:41:04.819915Z","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":"2026-08-05T17:41:05.041780Z","title":"Predicting multi-core system fmax by data-learning methodology,","venue":null,"work_id":"794e538b-b7d4-47be-86aa-e08433fdadf3","year":2010},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.824937Z"},"links":{"citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:98e5758d168c2ab77a75055d5596f5c16e27f11fce3e29b4c00756faf8e7ef83","observation_id":"8d140441-bd1d-4001-8768-dfb68718e03e","resolution":{"observed_at":"2026-08-05T17:41:05.046572Z","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":"2026-08-05T17:41:05.023532Z","title":"Data-efficient conformalized interval prediction of minimum operating voltage capturing process variations,","venue":null,"work_id":"05f441de-7522-48c0-a205-9bfae4d96199","year":null},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.830545Z"},"links":{"citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:c7f332c77c9bac17c0407b053d65c39aa1607cdbfbcbeed4fe106833c9aabba2","observation_id":"71785cc6-f2b6-47b2-a33f-5d64dc451d64","resolution":{"observed_at":"2026-08-05T17:41:05.030757Z","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":"2026-08-05T17:41:04.840064Z","title":"Correlation-based feature selection for machine learning,","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.840064Z"},"links":{"citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:b60c640e3971f20138d227811f543473f39e8b86efb3c7f0961fd9cfbcb0d5d2","observation_id":"d96bedbf-5767-4d89-94e7-0637eccbf55e","resolution":{"observed_at":"2026-08-05T17:41:04.840064Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-05T17:41:04.844730Z","title":"Adam: A method for stochastic optimization,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.844730Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:77ef8bbcaf75747d209dcbb56552a9f17041b3d960b1430a5cb10786343a7551","observation_id":"f7476278-eb19-4dd3-89a7-a4c74fa2a87e","resolution":{"observed_at":"2026-08-05T17:41:04.844730Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1505.00853","last_updated":"2015-11-27T06:58:14Z","snapshot_observed_at":"2026-07-06T04:16:54.272660Z","submitted_at":"2015-05-05T01:16:39Z","title":"Empirical Evaluation of Rectified Activations in Convolutional Network","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1505.00853","snapshot_observed_at":"2026-08-05T17:41:04.850445Z","title":"Empirical evaluation of rectified activations in convolutional network,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.850445Z"},"links":{"cited_paper":"/paper/1505.00853","citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:74f3bcefe22721ee3804c528af546aea2deb66e0198cb5d8a08688a6c15121aa","observation_id":"cdf64745-1d6d-448a-85d5-c8d10ed0ba2f","resolution":{"observed_at":"2026-08-05T17:41:04.850445Z","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":"2026-08-05T17:41:04.835695Z","title":"Available: https://doi.org/10.1145/3649329.3657338","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-05T17:41:04.835695Z"},"links":{"citing_paper":"/paper/2509.00035"},"observation_digest":"sha256:3c478e8eccdecd4ac8bc683b479904ada9303685897db63d898a9fb5014563ec","observation_id":"fde03b0f-2769-4881-b5a4-f0978235def2","resolution":{"observed_at":"2026-08-05T17:41:04.835695Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2509.00035","last_updated":"2025-08-21T23:13:55Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-05T17:41:04.301968Z","submitted_at":"2025-08-21T23:13:55Z","title":"Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing"},"reference_resolution":{"displayed":19,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":0,"verified_fuzzy":13},"total_outbound_references":19},"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 8 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2509.00035."}