{"id":"W2063000980","doi":"10.1016/j.bandc.2004.02.060","title":"Establishing visual category boundaries between objects: A PET study","year":2005,"lang":"en","type":"article","venue":"Brain and Cognition","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; McGill University; Jewish General Hospital; Institut Universitaire de Gériatrie de Montréal","funders":"","keywords":"Categorization; Psychology; Visual agnosia; Cognitive psychology; Agnosia; Categorical variable; Object (grammar); Neuroscience; Communication; Perception; Artificial intelligence; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002991665,0.0001147792,0.0001143161,0.00009266806,0.0006287149,0.0007812515,0.00006986458,0.00003570157,0.0001548668],"category_scores_gemma":[0.0004586143,0.0001105343,0.00002097973,0.0001748782,0.0001153041,0.0005867809,0.00004267808,0.0001406958,0.00009713017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000155386,"about_ca_system_score_gemma":0.00004964762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000161206,"about_ca_topic_score_gemma":0.00004847168,"domain_scores_codex":[0.9989617,0.000160654,0.0001566215,0.0003127751,0.0002249158,0.0001833029],"domain_scores_gemma":[0.9995975,0.0001711844,0.00005482793,0.00006233444,0.00003325609,0.00008088152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001874463,0.001141276,0.001378872,0.0001122585,0.0000192173,0.00006335546,0.03325328,0.000002814877,0.4068513,0.002600844,0.00249499,0.5518944],"study_design_scores_gemma":[0.02050271,0.0097414,0.07677848,0.0005812483,0.0005881182,0.000796767,0.1206587,0.008231471,0.5721477,0.0833336,0.1017418,0.004898124],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929512,0.00001557321,0.00121738,0.0008179754,0.00009945345,0.0002231311,0.00001109835,0.0001683695,0.004495814],"genre_scores_gemma":[0.9959499,0.000005993816,0.00008226225,0.003098531,0.0002776853,0.00001961505,0.00001547007,0.00001409776,0.0005364591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5469962,"threshold_uncertainty_score":0.7533626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05041851362329262,"score_gpt":0.3341137005457895,"score_spread":0.2836951869224968,"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."}}