{"id":"W2096741982","doi":"10.1109/iccv.1990.139628","title":"Analysis of facial images using physical and anatomical models","year":2002,"lang":"en","type":"article","venue":"","topic":"Face recognition and analysis","field":"Computer Science","cited_by":107,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Canadian Institute for Advanced Research","funders":"","keywords":"Computer science; Artificial intelligence; Computer vision; Face (sociological concept); Facial muscles; Set (abstract data type); Computer graphics; Graphics; Facial expression; Computer graphics (images); Pattern recognition (psychology)","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":[0.0001853261,0.0004331178,0.0003094126,0.001101054,0.0002230556,0.0008892938,0.0004579854,0.0004321898,0.003663353],"category_scores_gemma":[0.0006476028,0.0002836293,0.0005509686,0.000345727,0.0003737425,0.0007863962,0.0005769897,0.0003533849,0.001164727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003192103,"about_ca_system_score_gemma":0.0003679712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001894006,"about_ca_topic_score_gemma":0.001688355,"domain_scores_codex":[0.999842,0.00001856835,0.000007516527,0.00002984645,0.00008817785,0.00001383342],"domain_scores_gemma":[0.9998896,0.0000237066,0.00001514496,0.00002988182,0.00003361648,0.000008035192],"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":[0.0001358928,0.00005834763,0.001804149,0.0002271821,0.00007412457,0.0006967933,0.00020356,0.1355237,0.3146824,0.03596638,0.003673298,0.5069544],"study_design_scores_gemma":[0.00001241828,0.00007926062,0.005456514,0.00005009194,0.00004604127,0.001244151,0.0001360835,0.9017764,0.04770244,0.01789129,0.02556257,0.00004275317],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01243533,0.0002425929,0.9826313,0.0001117744,0.00002869728,0.00003850337,0.0001026189,0.0006367561,0.003772476],"genre_scores_gemma":[0.3169715,0.001440455,0.6719362,0.00008673798,0.00007369948,0.0001181561,0.0005192285,0.0002741604,0.00857996],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003663353,"threshold_uncertainty_score":0.01225519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0418742923722793,"score_gpt":0.269636803973841,"score_spread":0.2277625116015617,"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."}}