{"id":"W1274597083","doi":"10.1167/15.12.391","title":"Stimulus-specific regularities as a basis for perceptual induction","year":2015,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Rule induction; Stimulus (psychology); Learning rule; Perception; Artificial intelligence; Sequence learning; Sequence (biology); Mathematics; Pattern recognition (psychology); Psychology; Computer science; Cognitive psychology; Artificial neural network; Biology","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":[0.001993421,0.0003318606,0.0005937984,0.0005211679,0.0004210687,0.001540569,0.00141098,0.000859732,0.004103971],"category_scores_gemma":[0.01338102,0.0008214731,0.0007684921,0.0002642507,0.001814762,0.002431819,0.001831748,0.002136934,0.0005756313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008041058,"about_ca_system_score_gemma":0.0006513887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006610287,"about_ca_topic_score_gemma":0.0005746118,"domain_scores_codex":[0.9981054,0.0003417629,0.000137445,0.0006352877,0.0005712063,0.0002088346],"domain_scores_gemma":[0.9907317,0.004400136,0.001060865,0.002651771,0.0006788945,0.000476751],"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":[0.001731907,0.000787729,0.03180116,0.0008887846,0.0002800439,0.0006462966,0.001444463,0.02889278,0.6947013,0.08135275,0.001817803,0.155655],"study_design_scores_gemma":[0.0004103096,0.001484828,0.1864936,0.0001208799,0.0002383255,0.001095782,0.000363316,0.2257926,0.2460784,0.3308899,0.006779756,0.0002522029],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8601497,0.0004070168,0.1169878,0.0008305866,0.0001304222,0.0002325564,0.0001787627,0.0009821713,0.02010101],"genre_scores_gemma":[0.9774544,0.000106528,0.02090726,0.0001812303,0.00003034178,0.00009092247,0.0001837091,0.000167679,0.0008779378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004103971,"threshold_uncertainty_score":0.0137291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05403714166850158,"score_gpt":0.3141373637572878,"score_spread":0.2601002220887862,"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."}}