{"id":"W4321179324","doi":"10.1016/j.infbeh.2023.101827","title":"Coding infant engagement in the Face-to-Face Still-Face paradigm using deep neural networks","year":2023,"lang":"en","type":"article","venue":"Infant Behavior and Development","topic":"Child and Adolescent Psychosocial and Emotional Development","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University; Centre for Addiction and Mental Health; University of British Columbia","funders":"Brain and Behavior Research Foundation","keywords":"Artificial intelligence; Coding (social sciences); Computer science; Psychology; Observational study; Facial recognition system; Pattern recognition (psychology); Cognitive psychology; Statistics; Mathematics","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":[0.0002080504,0.0002534873,0.0002101037,0.0001905686,0.0000944964,0.0002622708,0.0002230135,0.0002873402,0.001705512],"category_scores_gemma":[0.001294243,0.00009854739,0.0001385102,0.0001733331,0.0001563135,0.0002889032,0.0004586278,0.0004413867,0.0002028803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002520466,"about_ca_system_score_gemma":0.0002591402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002355834,"about_ca_topic_score_gemma":0.005074586,"domain_scores_codex":[0.9998958,0.00002280149,0.000003075214,0.00002951753,0.0000220479,0.00002665965],"domain_scores_gemma":[0.999842,0.00007923813,0.00001727368,0.00001195985,0.00002464455,0.0000247439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001536114,0.0002820117,0.02328226,0.0002825976,0.00008742767,0.0003291104,0.0005941652,0.01355255,0.7148234,0.002815357,0.003049787,0.2393653],"study_design_scores_gemma":[0.00009751824,0.001022055,0.3166246,0.0001307359,0.000161011,0.0008541512,0.0007303093,0.555752,0.1108836,0.008095251,0.005547369,0.000101295],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9343026,0.00032444,0.05849047,0.0001855102,0.00008859398,0.0001218297,0.0008632974,0.0001749063,0.005448369],"genre_scores_gemma":[0.98347,0.000189376,0.0141265,0.00008906559,0.00002072395,0.00008332538,0.0003911926,0.0000432897,0.001586433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002355834,"threshold_uncertainty_score":0.005705476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06706958755923263,"score_gpt":0.3317384570195703,"score_spread":0.2646688694603376,"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."}}