{"id":"W2113588087","doi":"","title":"Classification of upper and lower face action units and facial expressions using hybrid tracking system and probabilistic neural networks","year":2006,"lang":"en","type":"article","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Artificial intelligence; Pattern recognition (psychology); Computer science; Probabilistic logic; Face (sociological concept); Feature (linguistics); Facial recognition system; Facial expression; Computer vision; Artificial neural network; Feature extraction; Facial motion capture; Tracking (education); Face detection; Feature vector; Probabilistic neural network; Time delay 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":[0.0008974543,0.0003580345,0.0003829092,0.0004909655,0.0001865184,0.0004678236,0.000405882,0.0004428373,0.0007590599],"category_scores_gemma":[0.00178008,0.0002568768,0.0003722214,0.0002788566,0.0002451321,0.0006069914,0.0002570976,0.0003397362,0.0003081324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004595382,"about_ca_system_score_gemma":0.0002973175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00310294,"about_ca_topic_score_gemma":0.002657738,"domain_scores_codex":[0.999549,0.00007950704,0.00002677352,0.0001415917,0.0001624022,0.00004072446],"domain_scores_gemma":[0.999487,0.0001749483,0.00006991411,0.00004872531,0.0001928473,0.00002645317],"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":[0.0006676154,0.0002468961,0.01750954,0.00008528522,0.000109587,0.0001178171,0.0001731374,0.06320795,0.1264638,0.00147052,0.001235111,0.7887129],"study_design_scores_gemma":[0.00001586426,0.0001241488,0.01341566,0.000007537771,0.000034424,0.00009778309,0.00002505123,0.9685825,0.016786,0.0005723668,0.0003203161,0.00001844951],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.289678,0.0001714091,0.7067398,0.00008678062,0.00004062445,0.00009609065,0.0000868741,0.001073092,0.002027334],"genre_scores_gemma":[0.8434899,0.0001102399,0.1539216,0.0000481903,0.00001862844,0.0001032088,0.000144062,0.00003039637,0.002133815],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00310294,"threshold_uncertainty_score":0.006169736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04955739329113534,"score_gpt":0.2624740382769427,"score_spread":0.2129166449858074,"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."}}