{"id":"W2786647102","doi":"10.1177/0301006618756809","title":"Unfamiliar Face Matching With Frontal and Profile Views","year":2018,"lang":"en","type":"article","venue":"Perception","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University","funders":"","keywords":"Matching (statistics); Face (sociological concept); Psychology; Contrast (vision); Identity (music); Facial recognition system; Cognitive psychology; Face perception; Artificial intelligence; Computer science; Pattern recognition (psychology); Perception; Mathematics; Linguistics; Statistics","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":[0.001709816,0.0004743241,0.0005237467,0.0003961941,0.0002099737,0.0009528247,0.0004434589,0.0007415006,0.008835542],"category_scores_gemma":[0.01772242,0.0002121504,0.0003777164,0.0001973056,0.0004273912,0.002314041,0.001144207,0.0003443345,0.001074031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002508589,"about_ca_system_score_gemma":0.0002379577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006660454,"about_ca_topic_score_gemma":0.000938483,"domain_scores_codex":[0.9986396,0.0003520213,0.0001359869,0.0003203125,0.0004196229,0.0001324434],"domain_scores_gemma":[0.9953427,0.002020537,0.0008392179,0.001112522,0.0004506622,0.0002343207],"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":[0.005903358,0.000703786,0.08261296,0.0008840511,0.0001861577,0.0008104398,0.002371783,0.001783511,0.6107277,0.002116813,0.002159737,0.2897398],"study_design_scores_gemma":[0.0003633201,0.007552326,0.744442,0.0002519681,0.0003703779,0.007963468,0.003430825,0.02666651,0.1896465,0.01067711,0.008403907,0.0002316628],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9754563,0.0002538709,0.01587048,0.00008590426,0.00006144244,0.000160983,0.0001363139,0.0001620452,0.007812701],"genre_scores_gemma":[0.9814942,0.000182741,0.0165243,0.0001284806,0.00002637904,0.00007435128,0.0001663056,0.00004880933,0.001354421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008835542,"threshold_uncertainty_score":0.02955788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05095901943752557,"score_gpt":0.2964270310750691,"score_spread":0.2454680116375435,"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."}}