{"id":"W3138800455","doi":"10.1037/xhp0000907","title":"Tuning the ensemble: Incidental skewing of the perceptual average through memory-driven selection.","year":2021,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Human Perception & Performance","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Selection (genetic algorithm); Computer science; Perception; Cognitive psychology; Artificial intelligence; Psychology; Neuroscience","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":[0.000932317,0.0001691081,0.0002828726,0.0002204287,0.0002018252,0.0007621893,0.0005939365,0.0002664992,0.001995284],"category_scores_gemma":[0.008103126,0.0002026609,0.0001609836,0.0001956434,0.0004262378,0.001006775,0.000983255,0.0005204982,0.0003567466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001701468,"about_ca_system_score_gemma":0.000179628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000390195,"about_ca_topic_score_gemma":0.0007258173,"domain_scores_codex":[0.9995634,0.00007913925,0.00002701598,0.0001716565,0.0001124447,0.00004624634],"domain_scores_gemma":[0.9972166,0.000838249,0.0004777818,0.001003613,0.0001808088,0.00028296],"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":[0.0008599939,0.0002919082,0.04216912,0.0002030234,0.0001852237,0.0002088027,0.0009191904,0.002606791,0.7332232,0.008072041,0.002316416,0.2089443],"study_design_scores_gemma":[0.0001464133,0.002480347,0.6535417,0.0001001428,0.0003541031,0.001487452,0.0007581407,0.06676695,0.2056397,0.05603825,0.01254188,0.00014487],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9571754,0.0003202269,0.03565034,0.0001652061,0.0001018562,0.00004685244,0.0001400193,0.0002978007,0.006102141],"genre_scores_gemma":[0.9923086,0.00009094018,0.006350928,0.0001105492,0.00002929931,0.0000275387,0.0001051259,0.00009012283,0.0008868322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001995284,"threshold_uncertainty_score":0.006674945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1336674840682772,"score_gpt":0.4033320792099174,"score_spread":0.2696645951416403,"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."}}