{"id":"W2001515769","doi":"10.1167/10.7.646","title":"The role of contour information in the spatial frequency tuning of upright and inverted faces","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Face recognition and analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Face (sociological concept); Set (abstract data type); Artificial intelligence; Orientation (vector space); Computer vision; Spatial frequency; Identification (biology); Pattern recognition (psychology); Aperture (computer memory); Mathematics; Computer science; Optics; Geometry; Physics; Acoustics; Linguistics","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":[0.0008006678,0.0002488714,0.0002206028,0.0006933592,0.0002496751,0.0005642053,0.0002384098,0.0004450956,0.002342159],"category_scores_gemma":[0.007850079,0.0003188319,0.0002196688,0.0001710974,0.0006067213,0.001010657,0.0007076572,0.0004277346,0.0002459222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002540578,"about_ca_system_score_gemma":0.000220772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001267937,"about_ca_topic_score_gemma":0.001260794,"domain_scores_codex":[0.9995265,0.00006432315,0.00003090529,0.0001210363,0.0001907772,0.00006654002],"domain_scores_gemma":[0.998001,0.0009411008,0.0003215138,0.0003085899,0.0003107463,0.0001170872],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00130775,0.00006216839,0.02346145,0.0001020345,0.00002921543,0.0001257617,0.0008578752,0.0005645655,0.9168411,0.001098671,0.0002226969,0.05532676],"study_design_scores_gemma":[0.00006792608,0.0005794668,0.8306803,0.00005163105,0.00006542662,0.000939704,0.0005006107,0.01168174,0.1491739,0.004719227,0.001467497,0.00007276564],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878018,0.000237315,0.008513173,0.00005149388,0.00002676879,0.00003406674,0.00007412092,0.00002679571,0.003234463],"genre_scores_gemma":[0.9938319,0.00008504796,0.005357272,0.00005359587,0.00001386635,0.00002449271,0.00008742901,0.00003256329,0.000513789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002342159,"threshold_uncertainty_score":0.007835329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005597807793723243,"score_gpt":0.2339601691476021,"score_spread":0.2283623613538789,"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."}}