{"id":"W2060089627","doi":"10.3758/s13414-010-0036-z","title":"Contrast and assimilation in categorization and exemplar production","year":2010,"lang":"en","type":"article","venue":"Attention Perception & Psychophysics","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University; Defence Research and Development Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Categorization; Contrast (vision); Stimulus (psychology); Artificial intelligence; Task (project management); Psychology; Cognitive psychology; Representation (politics); Computer science; Pattern recognition (psychology); Natural language processing","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":[0.001362474,0.0003779666,0.0006991223,0.0006283619,0.0004715176,0.002957486,0.0006992026,0.001359477,0.004679641],"category_scores_gemma":[0.01817166,0.0009666558,0.0005078887,0.0005312038,0.0008175611,0.003252174,0.001566852,0.00166222,0.0006681488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005591534,"about_ca_system_score_gemma":0.0004614664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001424847,"about_ca_topic_score_gemma":0.001239329,"domain_scores_codex":[0.9992066,0.0002025027,0.00003704253,0.0002136433,0.000250521,0.00008978619],"domain_scores_gemma":[0.9926817,0.005812005,0.0004490244,0.0003432884,0.0003655192,0.0003485349],"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":[0.00368823,0.0004244554,0.02079878,0.0002206039,0.0001070709,0.000692203,0.001606092,0.003470597,0.8431268,0.03720454,0.000791501,0.08786911],"study_design_scores_gemma":[0.0003507655,0.0008938214,0.6634731,0.0001125759,0.0001834617,0.002945229,0.0009257526,0.1034624,0.1236093,0.1005426,0.003296781,0.0002041833],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9745007,0.0005602534,0.01112237,0.000244125,0.0001364963,0.00002950336,0.0001086949,0.0001061395,0.01319173],"genre_scores_gemma":[0.9934,0.0001846377,0.00423498,0.00005160182,0.0000477522,0.00002113207,0.0001593237,0.000168242,0.001732416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004679641,"threshold_uncertainty_score":0.01565498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0218125570591561,"score_gpt":0.2797957437151691,"score_spread":0.2579831866560131,"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."}}