{"id":"W2888797767","doi":"10.1007/978-3-030-12738-1_12","title":"Automated Pain Detection in Facial Videos of Children Using Human-Assisted Transfer Learning","year":2019,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Pediatric Pain Management Techniques","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Nursing Research","keywords":"Computer science; Artificial intelligence; Facial Action Coding System; Transfer of learning; Coding (social sciences); Machine learning; Support vector machine; Facial expression; Facial recognition system; 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":[0.0002905348,0.0003710079,0.000259314,0.0005362859,0.0001110064,0.0002069376,0.0002895697,0.0003845959,0.002274807],"category_scores_gemma":[0.001146484,0.000073586,0.0002547061,0.0002520682,0.0001349145,0.0002464555,0.0004373259,0.0003159682,0.0006418383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001737138,"about_ca_system_score_gemma":0.0003323735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002766334,"about_ca_topic_score_gemma":0.004211755,"domain_scores_codex":[0.9998054,0.00004256314,0.000006531727,0.00004500509,0.00005475273,0.00004577223],"domain_scores_gemma":[0.9997051,0.0001260788,0.00002919814,0.00002186577,0.00008360633,0.00003401591],"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":[0.0006719876,0.0002603891,0.02064436,0.000260512,0.0000710173,0.0006698751,0.0002103694,0.006638269,0.1429623,0.0003280921,0.004427017,0.8228558],"study_design_scores_gemma":[0.00008251643,0.001415269,0.2300639,0.0001687896,0.000139518,0.004398216,0.000868385,0.6318025,0.1219128,0.001588274,0.00748175,0.00007810428],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8147407,0.001062441,0.1740825,0.0002079975,0.0001629768,0.0003567989,0.001636832,0.001582596,0.006167128],"genre_scores_gemma":[0.9182703,0.0005087807,0.07725586,0.00008469317,0.00006289278,0.0001507897,0.0009966454,0.00004623539,0.002623781],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002766334,"threshold_uncertainty_score":0.007610023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01313209233131819,"score_gpt":0.279919090646821,"score_spread":0.2667869983155028,"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."}}