{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003715425,0.0004449403,0.0006659338,0.0004153647,0.0001260915,0.0007058627,0.001355599,0.0002797435,0.0003052034],"category_scores_gemma":[0.0004513761,0.000420456,0.00008078062,0.0003419948,0.0001306064,0.0005800209,0.0005685826,0.0005053221,0.0004511705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000283051,"about_ca_system_score_gemma":0.00003598946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003309624,"about_ca_topic_score_gemma":0.00940772,"domain_scores_codex":[0.9974497,0.0002322708,0.0004979068,0.001031949,0.0003656029,0.0004226019],"domain_scores_gemma":[0.9969671,0.001377444,0.0001983439,0.00124982,0.00002816746,0.0001791176],"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":[0.00000278602,0.00006330184,0.000110927,0.00008112745,0.00005231681,0.0001644307,0.00003296845,0.000002988174,0.000003782311,0.000009473249,0.9917015,0.007774341],"study_design_scores_gemma":[0.0003779252,0.00003369374,0.0003784733,0.0003668487,0.0001087507,0.00001024924,0.00004326761,0.0004403994,0.00002338195,0.001779923,0.9958659,0.000571227],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001373538,0.001637955,0.001437316,0.0004970618,0.0002995715,0.0001707736,0.9957428,0.00005819138,0.00001896168],"genre_scores_gemma":[0.000101426,0.006236899,0.002398869,0.001209406,0.0001372882,0.00004354865,0.9898487,0.00001307674,0.00001072955],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.007203114,"threshold_uncertainty_score":0.9998247,"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."}}