{"as_of":"2026-08-17T00:29:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:28635608434c0296e573d26ca52b45dd485e6649f366bcc704e184c7ee466512","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":"2026-08-14T13:53:01.416799Z","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":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/1908.04186/citation-record","integrity":"/paper/1908.04186/integrity","json":"/paper/1908.04186/citation-record.json","paper":"/paper/1908.04186"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.684326Z","title":"(2015) A framework to automate assessment of upper-limb motor function impairment: A feasibility study","venue":null,"work_id":"0ee4b532-d4b9-4043-aad3-f9eb88dee4ba","year":2015},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.334089Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:35efeff3475c577697f29c4004cb30cb2ebe28d38f810d1873e922d02210d61d","observation_id":"bb16d6e7-0403-442c-a514-6b72b9aaaf39","resolution":{"observed_at":"2026-08-14T13:53:01.689009Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.668190Z","title":"(2008) Eeg source localization in focal epilepsy: where are we now? Epilepsia 49(2), 201–218","venue":null,"work_id":"11df2158-0e67-4f7a-acad-306ec322ea40","year":2008},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.339890Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:a0d75841bcd19274bc8f4fbab0fd0efb048603f3d06659a1fa8353ede22d2339","observation_id":"f21b24db-bc04-496f-922c-878e50473906","resolution":{"observed_at":"2026-08-14T13:53:01.673801Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.655895Z","title":"(1958) Report of the committee on methods of clinical examination in electroencephalography","venue":null,"work_id":"93ddfdb6-a36d-43f0-901b-c02a006ba409","year":1958},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.344852Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:6d0587ba5b0c49276d9f52ee243a8f4528df3891a10a90a6ad72073991f6e565","observation_id":"27c5d540-f780-4faa-9870-aabdbcd1a573","resolution":{"observed_at":"2026-08-14T13:53:01.660264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.643925Z","title":"(2007) 10/20, 10/10, and 10/5 systems revisited: their validity as relative head- surface-based positioning systems","venue":null,"work_id":"1e32dd02-66be-4152-a270-41d9795eec60","year":2007},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.349375Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:cc7c767db1043a4843b39064858458d30333e06000fec6bcbc6d7d844812e96d","observation_id":"62eb349c-8b7d-4597-a04e-0ace8db93521","resolution":{"observed_at":"2026-08-14T13:53:01.648049Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.631526Z","title":"(1993) The spatial location of eeg electrodes: locating the best-fitting sphere relative to cortical anatomy","venue":null,"work_id":"31e6d469-ec45-4a73-a8ce-49e375f97c09","year":1993},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.354037Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:d24f0e56ea3402cabec03a23970e66ebc43c30221133f23d5cbc5bf9ac94b1df","observation_id":"f7acde4e-6632-48f4-b88a-3a26131c5298","resolution":{"observed_at":"2026-08-14T13:53:01.635910Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.618422Z","title":"(1998) Scalp- recorded eeg localization in mri volume data","venue":null,"work_id":"77b139e4-40e4-451c-b7e0-6c3bbf26ea49","year":1998},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.358727Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:cb2891bef2fc91e3778a42bdad012cfd17a0083f4d716f624313a5d291210164","observation_id":"d379bfc8-d334-4358-b5d8-da178472b54c","resolution":{"observed_at":"2026-08-14T13:53:01.622560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.605736Z","title":"(2011) A single camera photogrammetry system for multi-angle fast localization of eeg electrodes","venue":null,"work_id":"075e87d2-6861-4300-8b38-8c2b8cd8198e","year":2011},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.363839Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:3c7f05170fe601e8ae00b9308173d5475c8f9066ec22b9e519cff923e5381970","observation_id":"84ee0a42-5290-41dc-bc55-314eaf9c6fb4","resolution":{"observed_at":"2026-08-14T13:53:01.610303Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.593743Z","title":"(2015) Using a motion capture system for spatial localization of eeg electrodes","venue":null,"work_id":"0a28093f-d234-4833-9480-a9c4486e3b9c","year":2015},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.368470Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:b38b5d7ac8f4dcdb04fa32157cfa26d2cbc551432bf21a2958ce60615a5c632c","observation_id":"b3d23587-9905-417c-b1d8-a56d148eae82","resolution":{"observed_at":"2026-08-14T13:53:01.597718Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.581329Z","title":"(2017) Photogrammetry-based head digitization for rapid and accurate localization of eeg electrodes and meg fiducial markers using a single digital slr camera","venue":null,"work_id":"92faf3de-9368-4965-a16d-ef94e5ab5866","year":2017},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.372679Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:1bf8406669e68e0eaebd67f375cca999f1d17ea3ef49d4bbea7ae8f855930f75","observation_id":"80ee8bfd-b00d-4c51-b867-9f9891cf6548","resolution":{"observed_at":"2026-08-14T13:53:01.585793Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.568665Z","title":"(2015) Faster r-cnn: Towards real-time object detection with region proposal networks","venue":null,"work_id":"29ce44a5-b15e-4f25-8977-8188c4d98893","year":2015},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.377083Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:84a3abf9f9fab36e6a198ac3b7418951e813c53e6fc3f6a15cc8cbd0b25bed02","observation_id":"cc1a33f7-f57e-4f47-988e-2351644a2e96","resolution":{"observed_at":"2026-08-14T13:53:01.573058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.554905Z","title":"(2019) Hyperface: A deep multi-task learning framework for face detection, landmark localization, pose estimation, and gender recognition","venue":null,"work_id":"827a772a-f2db-4e19-aa33-9335264ce137","year":2019},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.381054Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:7c898a609397de7dd52253246027e1e439588f644b691ae75fb05c9819bb166a","observation_id":"dc722604-5194-4c96-aec3-59d502196bf6","resolution":{"observed_at":"2026-08-14T13:53:01.559598Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.542923Z","title":"(2000) The OpenCV Library","venue":null,"work_id":"dd65a68c-4977-4d7b-a3c0-e1d5944f4d78","year":2000},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.386053Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:273a65269c62f22b03c96ec4a923b91bd2bf49b8db6f536e9455ab918eabb6c5","observation_id":"1c227f26-d847-4397-b80e-f45036df6578","resolution":{"observed_at":"2026-08-14T13:53:01.546928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.530322Z","title":"(2012) Non-orthogonal tool/flange and robot/world calibration","venue":null,"work_id":"d1e0d3e8-7563-4f6e-9e99-fdffabd7e076","year":2012},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.390589Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:c588b3a27b7d62c0093586fa54a88225f6266d535da82a007da4aa3acf58a17d","observation_id":"20d4b0b1-4d87-482a-b84f-a998b2c361fc","resolution":{"observed_at":"2026-08-14T13:53:01.534894Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.516590Z","title":"(2017) Densely connected convolutional networks","venue":null,"work_id":"eb4c6273-5246-4e95-b071-0eac1c508e8a","year":2017},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.394912Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:d8564369013bdb9efa3e2e55e2713aa1126dcdd4fdcd3744763ef6d9c33fa957","observation_id":"af21aef2-de1f-4722-a492-77d0706dded5","resolution":{"observed_at":"2026-08-14T13:53:01.521240Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.503689Z","title":"(2018) Squeeze-and-excitation networks","venue":null,"work_id":"1fa3aa26-c048-4830-950d-2c3b73b2e858","year":2018},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.399847Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:f3057b7cb5774687ab0c18cc4c06cda69f5ad887e1768d092d95eb9b53623113","observation_id":"c3e5d688-afbf-4324-8348-8025ea15cd4e","resolution":{"observed_at":"2026-08-14T13:53:01.507771Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.490819Z","title":"(2017) Automatic differentiation in PyTorch","venue":null,"work_id":"321e97af-df38-44d2-862a-e66113daac89","year":2017},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.404367Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:cab66edba4777401b67eebbdb30c2ddd7bd74353bb7d1a63f5ae88dc8bfe85a8","observation_id":"c865249e-263b-445e-97ae-c8617f61e5ba","resolution":{"observed_at":"2026-08-14T13:53:01.494862Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.477819Z","title":"(2015) A survey on multi-output regression","venue":null,"work_id":"2e77147d-aa83-48e1-95c5-830d21e0d661","year":2015},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.408496Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:28112d5b1d39abb821c2253360c543ebafa60c1baf65a0faf4610c9a9f54bd3b","observation_id":"580f5f28-0ab3-4a65-8908-e6142bff6537","resolution":{"observed_at":"2026-08-14T13:53:01.482301Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.464804Z","title":"(2014) Learning and transferring mid-level image representations using convolutional neural networks","venue":null,"work_id":"b12d39a9-168b-4b3c-ab4e-6df5518a3126","year":2014},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.412572Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:cacafded64be9781cb0303bba87522bb14fed735a62ec3ef8d94c89cb4376ede","observation_id":"4a8d3554-9fed-442c-b4bb-d89594d71314","resolution":{"observed_at":"2026-08-14T13:53:01.469437Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:53:01.448832Z","title":"(2018) Learning to compare: Relation network for few-shot learning","venue":null,"work_id":"61c0bdaf-4b91-4e09-bdf0-1f7a2ab33a47","year":2018},"citing_paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T13:53:01.416799Z"},"links":{"citing_paper":"/paper/1908.04186"},"observation_digest":"sha256:3cdc3398da04f672ff666bc26bd6aa7be8106f64e1a9d630bb55200e4658e8c1","observation_id":"a4415691-866b-4faf-93e7-6b98a120f06c","resolution":{"observed_at":"2026-08-14T13:53:01.455837Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.04186","last_updated":"2019-08-12T15:03:55Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-14T13:46:19.790489Z","submitted_at":"2019-08-12T15:03:55Z","title":"Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels"},"reference_resolution":{"displayed":19,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":19},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:1908.04186."}