{"id":"W3091725097","doi":"10.1109/iscas45731.2020.9180979","title":"Negative Label Guided Discriminative Canonical Correlation Analysis for Semi-Supervised and Semi-Paired Learning","year":2020,"lang":"en","type":"article","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Discriminative model; Artificial intelligence; Computer science; Canonical correlation; Pattern recognition (psychology); Class (philosophy); Semi-supervised learning; Exploit; Correlation; Machine learning; Process (computing); Supervised learning; Mathematics; Artificial neural network","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004626873,0.001733143,0.002104062,0.002121359,0.001258955,0.002006458,0.002941417,0.001561864,0.002820831],"category_scores_gemma":[0.01408263,0.0007489777,0.001426805,0.002471224,0.003033783,0.002617664,0.003157928,0.003100536,0.002043069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009364014,"about_ca_system_score_gemma":0.002406786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00227582,"about_ca_topic_score_gemma":0.003105633,"domain_scores_codex":[0.9943678,0.002445462,0.0002256191,0.001476176,0.001208373,0.000276592],"domain_scores_gemma":[0.991738,0.002861983,0.0009084746,0.00199013,0.002133378,0.0003680704],"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":[0.000408128,0.0004209277,0.004529779,0.0004104687,0.0002850886,0.0003323492,0.0006898491,0.2878917,0.01172228,0.07423906,0.01570545,0.603365],"study_design_scores_gemma":[0.000006879803,0.00003929247,0.0001979438,0.00001340301,0.00001176428,0.00007025267,0.00002882517,0.9827408,0.001864892,0.01392116,0.001084622,0.00002005337],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003845385,0.0001086978,0.9947943,0.00006399737,0.00002888293,0.00003892246,0.00004014527,0.0005292266,0.0005503615],"genre_scores_gemma":[0.3631657,0.0004245391,0.6294134,0.0003934621,0.0003293552,0.0005640639,0.001439131,0.0005376964,0.003732678],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004626873,"threshold_uncertainty_score":0.02446949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05965839286469624,"score_gpt":0.2867759447777587,"score_spread":0.2271175519130625,"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."}}