{"id":"W2796650365","doi":"10.1101/299933","title":"Multimodal evidence on shape and surface information in individual face processing","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Face (sociological concept); Computer science; Artificial intelligence; Modality (human–computer interaction); Face perception; Perception; Surface (topology); Pattern recognition (psychology); Consistency (knowledge bases); Computer vision; Psychology; Mathematics; Neuroscience","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006043346,0.0002378225,0.0002892549,0.0006469659,0.0001406328,0.0006399625,0.0002623058,0.0004256656,0.002400381],"category_scores_gemma":[0.002082604,0.0001890397,0.0002267275,0.0003406282,0.001138316,0.0009506372,0.0009286565,0.0004836893,0.0003172531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009305991,"about_ca_system_score_gemma":0.0001161014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003356329,"about_ca_topic_score_gemma":0.0003658604,"domain_scores_codex":[0.9998598,0.00003359798,0.00000823782,0.00002863742,0.00005071253,0.00001903347],"domain_scores_gemma":[0.9994005,0.0002012988,0.0001289114,0.000168893,0.00007050562,0.0000298803],"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":[0.0003613259,0.0000356416,0.003310732,0.0001190362,0.0000385232,0.0001433777,0.0002087153,0.002148342,0.9291645,0.002134807,0.0002047268,0.06213029],"study_design_scores_gemma":[0.00006382063,0.0005530334,0.3093771,0.0001360528,0.0001705541,0.002310493,0.000700288,0.06936616,0.5862927,0.02722782,0.003662252,0.0001397698],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9277657,0.0008315671,0.06648091,0.0003614186,0.00002063742,0.00001455429,0.0002224047,0.000236735,0.004066048],"genre_scores_gemma":[0.9890897,0.0002676554,0.01001448,0.00004560683,0.00001399324,0.000007090211,0.0001092539,0.00003925002,0.0004129559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002400381,"threshold_uncertainty_score":0.008030057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06080613209803237,"score_gpt":0.281829469776952,"score_spread":0.2210233376789196,"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."}}