{"id":"W2142206970","doi":"10.1152/jn.00576.2007","title":"Modifiability of Generalization in Dynamics Learning","year":2007,"lang":"en","type":"article","venue":"Journal of Neurophysiology","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":98,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Deafness and Other Communication Disorders","keywords":"Generalization; Workspace; Motor learning; Artificial intelligence; Computer science; Dynamics (music); Psychology; Mathematics; Neuroscience; Robot; Mathematical analysis","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":[0.000523474,0.0004629357,0.0005063547,0.0003905205,0.0002133834,0.0004696616,0.0005170166,0.0004517966,0.00315562],"category_scores_gemma":[0.004356022,0.0003111683,0.0005252065,0.0001573191,0.0007414515,0.001046137,0.001649077,0.001106431,0.0002473906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004415304,"about_ca_system_score_gemma":0.0003635195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007763085,"about_ca_topic_score_gemma":0.0007079239,"domain_scores_codex":[0.9994488,0.00005887919,0.00004220557,0.0001976247,0.0001601522,0.00009237943],"domain_scores_gemma":[0.9976528,0.0007065816,0.000294415,0.0009260034,0.0001654523,0.000254708],"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":[0.0004234301,0.0002430968,0.004933518,0.000111351,0.00007003292,0.0001172079,0.0001716567,0.008492944,0.9383013,0.001473226,0.0001291746,0.04553306],"study_design_scores_gemma":[0.0001522449,0.003884564,0.3685328,0.000074873,0.0001644372,0.001425204,0.0002358055,0.06475925,0.541344,0.01432613,0.004981053,0.0001196961],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9842907,0.0001937526,0.01240716,0.00008767779,0.00001761354,0.00003737667,0.00008362906,0.0003545594,0.002527424],"genre_scores_gemma":[0.9972831,0.00005890819,0.001877476,0.00002634464,0.000006193182,0.0000231007,0.0000662291,0.00004085961,0.0006178794],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00315562,"threshold_uncertainty_score":0.01055658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0250971321708932,"score_gpt":0.2701618343323408,"score_spread":0.2450647021614475,"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."}}