{"id":"W4312700750","doi":"10.1007/978-3-031-16990-8_13","title":"Support Vector Machine","year":2022,"lang":"en","type":"book-chapter","venue":"International series in management science/operations research/International series in operations research & management science","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Public Health Ontario; York University","funders":"","keywords":"Computer science; Vector (molecular biology); Support vector machine; Artificial intelligence; Biology","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":[0.0006625967,0.001295976,0.001081152,0.001404986,0.0003717184,0.00149768,0.001020989,0.0008820241,0.01950191],"category_scores_gemma":[0.003093116,0.0003381628,0.000663996,0.001716186,0.0002441145,0.001410819,0.0008014388,0.001269591,0.01740303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002775661,"about_ca_system_score_gemma":0.0006358293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001329076,"about_ca_topic_score_gemma":0.001261817,"domain_scores_codex":[0.9991924,0.0001233774,0.00006407827,0.0002086772,0.0003546698,0.0000567774],"domain_scores_gemma":[0.9990155,0.0002786114,0.00006375151,0.0001679967,0.0004399437,0.00003425323],"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":[0.00008396803,0.0000941589,0.0004059753,0.000135077,0.0000511057,0.00003254336,0.00001109655,0.01455715,0.002488969,0.00429015,0.03678844,0.9410614],"study_design_scores_gemma":[0.00004810201,0.0002729646,0.002064689,0.0001245841,0.00006968119,0.0002306034,0.00006281521,0.8589231,0.0163347,0.02378845,0.09801805,0.00006231914],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01442711,0.00544,0.9226815,0.0009786283,0.001328367,0.0003118561,0.004507137,0.01479843,0.03552693],"genre_scores_gemma":[0.2580487,0.004464134,0.6199182,0.0007607795,0.0009016147,0.0005752976,0.02250336,0.001024978,0.09180299],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01950191,"threshold_uncertainty_score":0.06524044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06153818047174198,"score_gpt":0.3960111665633341,"score_spread":0.3344729860915922,"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."}}