{"id":"W2088382195","doi":"10.1167/5.8.979","title":"Sentivitity to the spacing of features in novel objects after learning individuals vs. categories","year":2005,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University; McMaster University","funders":"","keywords":"Categorization; Categorical variable; Psychology; Object (grammar); Set (abstract data type); Artificial intelligence; Group (periodic table); Cognitive neuroscience of visual object recognition; Combinatorics; Pattern recognition (psychology); Cognitive psychology; Communication; Mathematics; Computer science; Statistics; Physics","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":[0.0003972133,0.0002859042,0.00050855,0.0001819751,0.0001541951,0.000766673,0.0004531686,0.0006075818,0.003338917],"category_scores_gemma":[0.001944794,0.0002580138,0.0002810865,0.0001090141,0.0007596847,0.0006103383,0.0006918503,0.001438433,0.0003553302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002777718,"about_ca_system_score_gemma":0.0002047469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008815083,"about_ca_topic_score_gemma":0.0008794533,"domain_scores_codex":[0.9995784,0.00004351211,0.00003059153,0.0001700155,0.0001040555,0.00007337017],"domain_scores_gemma":[0.9986224,0.000447086,0.0002716,0.0002153158,0.0001421162,0.0003015564],"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":[0.002770568,0.00170348,0.02309006,0.0001473497,0.0001025325,0.0002696007,0.0008041295,0.001604116,0.9385698,0.0004039499,0.0004152688,0.03011926],"study_design_scores_gemma":[0.0002765247,0.01745087,0.5478652,0.00006695972,0.0003016979,0.0007621071,0.001440485,0.02543,0.3962068,0.005829972,0.004214391,0.0001549407],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989703,0.00002650243,0.0002721043,0.00005289232,0.00002360981,0.000009290248,0.00003618202,0.00001387988,0.0005953118],"genre_scores_gemma":[0.9964385,0.00007710585,0.000765316,0.00009434484,0.000007459217,0.00003662652,0.0001624789,0.00002270235,0.002395426],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003338917,"threshold_uncertainty_score":0.01116973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02159629823336872,"score_gpt":0.3058038807380007,"score_spread":0.284207582504632,"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."}}