{"id":"W4391324453","doi":"10.1167/jov.24.1.10","title":"Asymmetric stimulus representations bias visual perceptual learning","year":2024,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute; Université de Montréal; McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Montréal","keywords":"Stimulus (psychology); Visual cortex; Perception; Perceptual learning; Psychology; Cognitive psychology; Visual perception; Motion perception; Artificial intelligence; Neuroscience; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006383279,0.0001026829,0.0001483802,0.00063185,0.0002122098,0.0003547657,0.0001562552,0.0000649876,0.000618419],"category_scores_gemma":[0.0015991,0.00007838922,0.0001425951,0.0009663537,0.00004547013,0.0005953434,0.00004757252,0.0005271945,0.0003781477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005585213,"about_ca_system_score_gemma":0.00009043785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002224529,"about_ca_topic_score_gemma":2.661978e-7,"domain_scores_codex":[0.9983895,0.0002425249,0.0003980222,0.0002042911,0.0006053178,0.0001602964],"domain_scores_gemma":[0.9991335,0.0004243198,0.0001533993,0.00006626783,0.0000980375,0.0001244726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004948416,0.0001134312,0.00004843739,0.00003083638,0.000004845222,0.0001458696,0.001230336,0.0008733954,0.8158367,0.0005690058,0.00306656,0.1780311],"study_design_scores_gemma":[0.003120263,0.01278306,0.02050614,0.002188771,0.0002635474,0.004894385,0.006516326,0.5268595,0.2527095,0.007554927,0.1612997,0.001303886],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9754699,0.0003770068,0.01864818,0.0007824905,0.001700658,0.00006624767,0.000001548687,0.0001155698,0.002838413],"genre_scores_gemma":[0.9962496,0.0002331565,0.000616473,0.0002548444,0.0003384169,5.808419e-7,7.419356e-7,0.00002041147,0.002285742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5631272,"threshold_uncertainty_score":0.6771255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08967262062716735,"score_gpt":0.4141676232448684,"score_spread":0.3244950026177011,"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."}}