{"id":"W3006649263","doi":"10.1109/icb45273.2019.8987241","title":"Audio-Visual Kinship Verification in the Wild","year":2019,"lang":"en","type":"article","venue":"","topic":"Face recognition and analysis","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Kinship; Computer science; Artificial intelligence; Modal; Natural language processing; Speech recognition; 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":[0.0008409515,0.0005077207,0.0006452258,0.0009466341,0.0004064481,0.0005269513,0.0009212106,0.0008820267,0.002413678],"category_scores_gemma":[0.001625376,0.000186002,0.0003738049,0.0004295607,0.0004485973,0.001184185,0.001176869,0.0005794968,0.001333137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003721384,"about_ca_system_score_gemma":0.0003586304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003579253,"about_ca_topic_score_gemma":0.01028712,"domain_scores_codex":[0.9992481,0.000166134,0.00002913979,0.0002708095,0.0001922588,0.00009355473],"domain_scores_gemma":[0.9992326,0.0002105162,0.00008786866,0.0002096165,0.0001917263,0.00006756814],"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":[0.001363307,0.0005738685,0.02721349,0.000492721,0.0002660927,0.001050229,0.0003048662,0.05324191,0.1340277,0.003035063,0.0193908,0.75904],"study_design_scores_gemma":[0.00006763641,0.0004630625,0.06787152,0.00009592011,0.000104112,0.002046905,0.0009199185,0.8323121,0.07546467,0.01009448,0.01049138,0.00006839513],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6724726,0.001821621,0.3062539,0.0003757811,0.0003213588,0.000210963,0.004772593,0.002769708,0.01100148],"genre_scores_gemma":[0.9058902,0.0002971305,0.08075204,0.0001644841,0.00005292816,0.00006862868,0.007414235,0.00005670364,0.005303652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003579253,"threshold_uncertainty_score":0.008074582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01420025138134312,"score_gpt":0.2507055965077537,"score_spread":0.2365053451264106,"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."}}