{"id":"W2104752854","doi":"","title":"Metric Learning by Collapsing Classes","year":2005,"lang":"en","type":"article","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":665,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Mahalanobis distance; Metric (unit); Metric space; Mathematics; Intrinsic metric; Artificial intelligence; Feature vector; Computer science; Convex metric space; Mathematical optimization; Pattern recognition (psychology); Algorithm; Discrete mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009226784,0.00004780667,0.0000516698,0.00008467222,0.0001030864,0.0001275647,0.0001782965,0.00002833786,0.0001455128],"category_scores_gemma":[0.00003687133,0.00003952894,0.00002041484,0.0003991243,0.000006203981,0.0004701844,0.00006099235,0.00006855514,0.0004810611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001608356,"about_ca_system_score_gemma":0.00001276926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001015935,"about_ca_topic_score_gemma":0.000002504967,"domain_scores_codex":[0.9994907,0.00002731105,0.00008055934,0.0001448206,0.0001293265,0.000127277],"domain_scores_gemma":[0.9997425,0.0000625712,0.00002598235,0.00009494559,0.00002978487,0.0000442001],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001547085,0.00005272569,0.0005673572,0.000003800747,0.000005890948,0.000001543823,0.0001596589,0.0005469657,0.02011236,0.001701491,0.3438499,0.6329967],"study_design_scores_gemma":[0.0002382418,0.00004530068,0.0001458187,0.00001356888,0.000002238446,0.000006137691,0.00008341924,0.109608,0.1066431,0.0002186944,0.7828297,0.0001656982],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04085769,0.0005002381,0.876849,0.003441351,0.000190225,0.000067498,3.4135e-7,0.0004605833,0.07763307],"genre_scores_gemma":[0.9115385,0.00003573097,0.07475791,0.0009978327,0.00004598752,0.000003719403,0.000002289001,0.000003911322,0.01261414],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8706808,"threshold_uncertainty_score":0.6183228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01189598646681285,"score_gpt":0.2456906142936362,"score_spread":0.2337946278268233,"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."}}