{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001408358,0.00004883591,0.0001666046,0.0001369039,0.00002068978,0.000002967618,0.00009908889,0.00003334689,0.000006393839],"category_scores_gemma":[0.0008005851,0.00004093956,0.00005056382,0.0001713382,0.00004747475,0.00009091505,0.00001483488,0.0001818306,0.000001047394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002745958,"about_ca_system_score_gemma":0.00002159623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009399769,"about_ca_topic_score_gemma":0.000003754741,"domain_scores_codex":[0.9990903,0.0001978723,0.000407667,0.0000886761,0.0001097813,0.0001056747],"domain_scores_gemma":[0.9992592,0.0002284559,0.0003588753,0.00005722047,0.00006894596,0.00002733082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000142451,0.00005189264,0.0005112655,0.000006139239,6.970845e-7,0.00002415991,0.00005984033,0.07385462,0.9215644,0.001066541,2.342828e-7,0.002717751],"study_design_scores_gemma":[0.001150305,0.001166739,0.66949,0.00001730989,0.000008408801,0.00006823921,0.00005723833,0.2920169,0.03238354,0.003347255,0.0001900745,0.0001040506],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906515,0.000003926444,0.008891564,0.00006905852,0.0002190199,0.00003819797,5.22988e-7,0.000003292313,0.0001229506],"genre_scores_gemma":[0.9996263,0.00002645142,0.0001395707,0.0001152028,0.00006342743,1.681491e-7,3.344387e-7,0.000004853147,0.00002365453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8891808,"threshold_uncertainty_score":0.1669467,"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."}}