{"id":"W7027493629","doi":"","title":"Channel selection for test-time adaptation under distribution shift","year":2023,"lang":"en","type":"other","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Mila - Quebec Artificial Intelligence Institute","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Fondation de l'Association des radiologistes du Québec; Institut de Valorisation des Données; Canadian Institute for Advanced Research","keywords":"Normalization (sociology); Robustness (evolution); Domain adaptation; Channel (broadcasting); Adaptation (eye); Generalization","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002596885,0.001389033,0.0009709755,0.0005862984,0.0006304804,0.001048226,0.00258297,0.001162334,0.007219156],"category_scores_gemma":[0.0106374,0.0004323722,0.0007152042,0.0008075617,0.001229676,0.002096578,0.002136933,0.003221749,0.003528493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001169526,"about_ca_system_score_gemma":0.002582202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01170455,"about_ca_topic_score_gemma":0.01511373,"domain_scores_codex":[0.9987131,0.0004407301,0.00004864011,0.0004042747,0.0002077597,0.0001854336],"domain_scores_gemma":[0.9970635,0.001088926,0.0001447998,0.0009653534,0.0005525378,0.0001849212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009416685,0.0004257127,0.005547727,0.0001426098,0.0001672851,0.0002334955,0.0001789837,0.4243583,0.01623146,0.01435692,0.03531973,0.5020961],"study_design_scores_gemma":[0.00002875679,0.00004991848,0.0006476662,0.00001181972,0.00001948956,0.00004321399,0.00002434165,0.9788193,0.006821122,0.01081572,0.002695356,0.00002329844],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04714199,0.0009532411,0.9277642,0.001035985,0.0003989388,0.0001778692,0.001147113,0.01403174,0.007348869],"genre_scores_gemma":[0.7239253,0.0004618041,0.2506547,0.001333859,0.0003279153,0.0004680562,0.004126041,0.00154803,0.01715436],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01170455,"threshold_uncertainty_score":0.02415049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009174502540552618,"score_gpt":0.1799361529272361,"score_spread":0.1707616503866835,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}