{"id":"W3162442677","doi":"10.31234/osf.io/r659w","title":"Reconsidering the Automaticity of Visual Statistical Learning","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Statistics Education and Methodologies","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Automaticity; Contrast (vision); Implicit learning; Cognitive psychology; Statistical learning; Task (project management); Sequence learning; Computer science; Process (computing); Psychology; Measure (data warehouse); Artificial intelligence; Cognition","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":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001529636,0.0001782599,0.0004725442,0.00006402976,0.00005602433,0.00004375324,0.0002243218,0.0001623383,0.001288144],"category_scores_gemma":[0.01780809,0.0001182461,0.00007816102,0.00004559956,0.0001277008,0.00001257777,0.0004387378,0.0006785056,0.00004803042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003687924,"about_ca_system_score_gemma":0.0002690823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002368747,"about_ca_topic_score_gemma":0.000009652925,"domain_scores_codex":[0.9982113,0.0006077543,0.0005375224,0.0002338973,0.0002347228,0.0001748208],"domain_scores_gemma":[0.9835865,0.01544664,0.0004159569,0.0003714869,0.0001425642,0.00003684781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002864243,0.000259921,0.00253802,0.00375688,0.0003531504,0.000003441967,0.007010079,0.001490214,0.0001695042,0.8986579,0.06405515,0.02167711],"study_design_scores_gemma":[0.000133036,0.00005351341,0.001853204,0.0001799215,0.0001341997,0.000007427741,0.003142525,0.02790376,0.00140133,0.9642544,0.000692256,0.0002444687],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0492037,0.00003864142,0.937044,0.0002857494,0.001550479,0.0004498322,0.0000478127,0.000172595,0.01120717],"genre_scores_gemma":[0.2274959,0.00003519514,0.7689965,0.00007101047,0.00006876836,0.00003156199,0.00002166859,0.00003066454,0.003248779],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1782922,"threshold_uncertainty_score":0.9996248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5278441578838118,"score_gpt":0.4860846890632295,"score_spread":0.04175946882058229,"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."}}