{"id":"W2151614338","doi":"10.1109/isspit.2006.270764","title":"Pain Recognition Using Artificial Neural Network","year":2006,"lang":"en","type":"article","venue":"","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Computer science; Artificial intelligence; Facial expression; Feature extraction; Backpropagation; Pattern recognition (psychology); Artificial neural network; Feature (linguistics); Face (sociological concept); Facial recognition system; Face detection; Computer vision; Detector; Three-dimensional face recognition; Speech recognition","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":[0.000341526,0.0003873278,0.0004039522,0.000431181,0.0001775226,0.0005781972,0.0005610903,0.0006452694,0.00178091],"category_scores_gemma":[0.0009922987,0.0001834229,0.0003075794,0.000442378,0.0001536553,0.0004601396,0.0002257159,0.0004459633,0.0006019716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003726704,"about_ca_system_score_gemma":0.00027195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00343487,"about_ca_topic_score_gemma":0.003480292,"domain_scores_codex":[0.9998156,0.00003519788,0.00001454481,0.00004828461,0.00006107146,0.00002535283],"domain_scores_gemma":[0.9997773,0.0000786545,0.00002854279,0.00001683446,0.00009206601,0.00000676133],"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":[0.0002864742,0.0002094417,0.003308281,0.00017336,0.0001263192,0.0001703185,0.00004580816,0.2161549,0.04772656,0.002231292,0.004148394,0.7254188],"study_design_scores_gemma":[0.000007230977,0.0000398043,0.001253413,0.00001054886,0.00001392297,0.00003639428,0.000006451488,0.9917477,0.005192039,0.0008970054,0.0007878403,0.000007585518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.100252,0.001914077,0.8857642,0.0005750215,0.0002527572,0.0001176537,0.0003054469,0.002955483,0.007863355],"genre_scores_gemma":[0.7757965,0.0009516253,0.2145835,0.0002573242,0.0001094143,0.0001982759,0.0004622998,0.00004436123,0.007596633],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00343487,"threshold_uncertainty_score":0.006829739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08595519455571393,"score_gpt":0.3181558221684621,"score_spread":0.2322006276127482,"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."}}