{"id":"W2952836486","doi":"10.1167/18.8.12","title":"Bayesian adaptive stimulus selection for dissociating models of psychophysical data","year":2018,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"De Beers (Canada)","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Computer science; Stimulus (psychology); Model selection; Bayesian probability; Perception; Two-alternative forced choice; Psychophysics; Artificial intelligence; Noise (video); Algorithm; Pattern recognition (psychology); Machine learning; Mathematics; Statistics; Psychology; Cognitive psychology","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":[0.009837893,0.001021616,0.001176236,0.001101088,0.000549018,0.0008866345,0.002038008,0.001195601,0.004214607],"category_scores_gemma":[0.03328728,0.0008477366,0.001122435,0.0007505818,0.001155129,0.001833947,0.002287644,0.002387983,0.000647239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001043857,"about_ca_system_score_gemma":0.001317979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008825185,"about_ca_topic_score_gemma":0.001329318,"domain_scores_codex":[0.9955248,0.002795296,0.0002343276,0.0006203833,0.0006653806,0.0001597326],"domain_scores_gemma":[0.9857474,0.0110984,0.0007029747,0.001435553,0.0007065093,0.0003092052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002810759,0.0010083,0.009829437,0.0005449909,0.0005336009,0.0002560775,0.0008326119,0.1982445,0.09468682,0.05624514,0.002274247,0.6327335],"study_design_scores_gemma":[0.0001395938,0.0002182524,0.002096814,0.00001727826,0.00003235542,0.00008092864,0.00002353564,0.96471,0.01044236,0.02127028,0.0009290428,0.00003950512],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02423071,0.00005299177,0.9741876,0.00005728766,0.00001700599,0.000227614,0.00003095334,0.0007601663,0.0004357513],"genre_scores_gemma":[0.205702,0.00003407878,0.792912,0.0001509658,0.00001660985,0.0006164395,0.0001222461,0.0001715089,0.0002741627],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009837893,"threshold_uncertainty_score":0.05202836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1291958560679263,"score_gpt":0.4182639475298982,"score_spread":0.2890680914619719,"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."}}