{"id":"W4252168990","doi":"10.1037/e574242014-152","title":"Age Similarities in Recognizing Threat from Faces and Diagnostic Cues","year":2014,"lang":"en","type":"dataset","venue":"PsycEXTRA Dataset","topic":"Face recognition and analysis","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"National Institutes of Health","keywords":"Sensory cue; Evolutionary biology; Biology; Artificial intelligence; Communication; Cognitive psychology; Psychology; Computer science","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":[0.001491119,0.001306558,0.0008592301,0.001501608,0.0005987994,0.001071149,0.001554478,0.0009813472,0.008891355],"category_scores_gemma":[0.005729613,0.0002461495,0.0009254302,0.001106968,0.0003064949,0.0006983405,0.001080799,0.000851198,0.008424458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008962286,"about_ca_system_score_gemma":0.0006923638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01693911,"about_ca_topic_score_gemma":0.02917183,"domain_scores_codex":[0.9989711,0.0001512052,0.0001462635,0.0003473652,0.000253919,0.0001302507],"domain_scores_gemma":[0.9984108,0.0005341536,0.0002116027,0.000357028,0.0003997049,0.00008672324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00212041,0.0004113714,0.1089016,0.003388107,0.0004347927,0.0003210408,0.000296114,0.00219102,0.004986553,0.0007923787,0.7463539,0.1298027],"study_design_scores_gemma":[0.0006049293,0.0003686702,0.5803347,0.0008100219,0.0005328843,0.002054733,0.0007282023,0.01286654,0.0073556,0.002411247,0.3917244,0.0002081209],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.08852502,0.003552229,0.002001387,0.0007311808,0.0004607374,0.0003923888,0.8967412,0.00113208,0.006463879],"genre_scores_gemma":[0.07578506,0.0006412575,0.00356791,0.0001941588,0.0000706549,0.0007844123,0.915861,0.00006290532,0.003032627],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01693911,"threshold_uncertainty_score":0.03368104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02857820644390761,"score_gpt":0.2762719400106096,"score_spread":0.247693733566702,"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."}}