{"id":"W4247419420","doi":"10.1109/ijcnn.2006.1716419","title":"Appearance-based Pain Recognition from Video Sequences","year":2006,"lang":"en","type":"article","venue":"The 2006 IEEE International Joint Conference on Neural Network Proceedings","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"University of British Columbia; University of Northern British Columbia","keywords":"Artificial intelligence; Computer vision; Computer science; Face (sociological concept); Feature (linguistics); Facial recognition system; Biometrics; Pattern recognition (psychology); Feature vector; Feature extraction; Face detection; Three-dimensional face recognition","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002891399,0.0004046558,0.0004807731,0.001204,0.0001139564,0.0004125892,0.0003649166,0.0004449946,0.00123649],"category_scores_gemma":[0.001698003,0.0001106335,0.0002483818,0.0005990064,0.0001596056,0.0004440313,0.000274957,0.0003171019,0.0008588024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001549055,"about_ca_system_score_gemma":0.0001429622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00103696,"about_ca_topic_score_gemma":0.001327688,"domain_scores_codex":[0.9996523,0.00005586967,0.00002050475,0.00005111828,0.0001829825,0.00003718182],"domain_scores_gemma":[0.9995376,0.00008918619,0.00007537532,0.00003812378,0.0002241411,0.00003563121],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009029407,0.0001177791,0.003722623,0.0003513259,0.0000463965,0.0004869635,0.00009307008,0.006193585,0.3069128,0.0008558064,0.001988658,0.6783281],"study_design_scores_gemma":[0.00007851885,0.001410862,0.0809415,0.0001913709,0.0001429574,0.004613263,0.0002922893,0.6392903,0.2602434,0.002698803,0.009977194,0.0001195828],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2061025,0.002250355,0.783207,0.0001968428,0.0003139125,0.0003336153,0.0008291194,0.002031169,0.004735626],"genre_scores_gemma":[0.6371691,0.001807677,0.3557903,0.0001350917,0.0002082958,0.0001971313,0.001154599,0.00008819074,0.003449657],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00123649,"threshold_uncertainty_score":0.004136503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03596230309010388,"score_gpt":0.2314801203264261,"score_spread":0.1955178172363222,"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."}}