{"id":"W2158866455","doi":"10.1111/j.0956-7976.2004.00768.x","title":"Object Updating and the Flash-Lag Effect","year":2004,"lang":"en","type":"article","venue":"Psychological Science","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Illusion; Object (grammar); Perception; Computer vision; Optical illusion; Flash (photography); Psychology; Feature (linguistics); Representation (politics); Artificial intelligence; Corollary; Lag; Motion (physics); Motion perception; Path (computing); Cognitive psychology; Communication; Computer science; Mathematics; Optics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001642446,0.0001018152,0.0001108948,0.0000399654,0.0007781073,0.0002516501,0.0005096691,0.00004061663,0.0001126747],"category_scores_gemma":[0.001855077,0.00004913316,0.00003233048,0.0007396555,0.002033474,0.0002070202,0.0001135348,0.0001926247,0.0002884117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002067868,"about_ca_system_score_gemma":0.00001469639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003657012,"about_ca_topic_score_gemma":6.618353e-7,"domain_scores_codex":[0.99848,0.0001463746,0.0001256596,0.0005467398,0.0003887805,0.0003124996],"domain_scores_gemma":[0.9993877,0.0002419179,0.00005111715,0.0001913327,0.00001622983,0.000111637],"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":[0.00007965344,0.0000511753,0.00007246622,0.00000429724,2.637235e-7,0.000006360334,0.0004651754,0.00001897092,0.9026742,0.0632944,0.00002528903,0.03330776],"study_design_scores_gemma":[0.009616753,0.002517702,0.03234183,0.0001089011,0.000019183,0.000748535,0.0003525529,0.001395469,0.7006277,0.2497227,0.001680676,0.0008679595],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9599423,0.00001428534,0.001236292,0.001539087,0.0002864989,0.0001817827,5.356366e-7,0.0001127746,0.03668638],"genre_scores_gemma":[0.9942785,0.00002252054,0.0006240092,0.004935626,0.00004220107,0.00001445154,7.260417e-8,0.000003497686,0.00007912507],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2020464,"threshold_uncertainty_score":0.749242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05725894312411384,"score_gpt":0.3965564488690843,"score_spread":0.3392975057449704,"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."}}