{"id":"W2787719532","doi":"10.1167/16.12.27","title":"Statistical learning creates novel object associations via transitive relations","year":2016,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Transitive relation; Categorical variable; Statistical learning; Object (grammar); Hierarchy; Sequence (biology); Base (topology); Superordinate goals; Artificial intelligence; Combinatorics; Task (project management); Psychology; Computer science; Mathematics; Communication; Social psychology; Machine learning","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":[0.0007130835,0.000316942,0.0002678161,0.0003882916,0.0003400939,0.0009422963,0.0006500361,0.0003287541,0.001985893],"category_scores_gemma":[0.004477684,0.0005163983,0.0005762307,0.0002569033,0.001184857,0.002464915,0.001297679,0.0009280837,0.0002721619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004692394,"about_ca_system_score_gemma":0.0003992993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007981395,"about_ca_topic_score_gemma":0.00128539,"domain_scores_codex":[0.9993628,0.000119484,0.00003826141,0.00027888,0.000146639,0.00005400007],"domain_scores_gemma":[0.9965634,0.001345658,0.000716345,0.001017424,0.0001751613,0.000182045],"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":[0.0005480024,0.0004827796,0.03733892,0.0004415847,0.0001895432,0.0007111461,0.002137229,0.02448564,0.5351256,0.06762566,0.001357448,0.3295565],"study_design_scores_gemma":[0.0001386514,0.001673248,0.09925032,0.00009672005,0.0002355242,0.001814065,0.0008856758,0.3566967,0.2539709,0.2695598,0.01549247,0.0001858592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7896622,0.0001159899,0.2013729,0.0002232038,0.00003597067,0.00005712445,0.0001106847,0.0006331201,0.007788847],"genre_scores_gemma":[0.9525299,0.00009461659,0.04605418,0.00006304037,0.00001441923,0.00002963761,0.0001673527,0.00006481419,0.0009820444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001985893,"threshold_uncertainty_score":0.006643414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01285443688363099,"score_gpt":0.2843856205891352,"score_spread":0.2715311837055042,"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."}}