{"id":"W4221048398","doi":"10.1016/j.neuroimage.2022.119111","title":"Brain-spinal cord interaction in long-term motor sequence learning in human: An fMRI study","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Université de Montréal; McGill University; Montreal Neurological Institute and Hospital; Mila - Quebec Artificial Intelligence Institute; Institut Universitaire de Gériatrie de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Neuroscience; Spinal cord; Cerebellum; Sequence learning; Psychology; Motor learning","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001958348,0.0001814434,0.0001472956,0.0002724373,0.0001372482,0.0001682674,0.000207246,0.0003909742,0.00110052],"category_scores_gemma":[0.0004079615,0.0001274031,0.0001276081,0.0001738078,0.0003322962,0.0002162235,0.0001452948,0.0002316992,0.0001343175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001311738,"about_ca_system_score_gemma":0.000147818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001349944,"about_ca_topic_score_gemma":0.002723275,"domain_scores_codex":[0.9999535,0.00001116277,0.000001862074,0.00001597207,0.000006334266,0.00001115049],"domain_scores_gemma":[0.9999067,0.00004470835,0.00001848137,0.00000777254,0.000008902801,0.00001343825],"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":[0.0007444883,0.0003864112,0.01485859,0.0003760021,0.0001083385,0.001446357,0.0005863223,0.001335448,0.9310799,0.0006667889,0.0003415516,0.04806972],"study_design_scores_gemma":[0.00006519406,0.001342984,0.9240072,0.00005307548,0.0001727453,0.004141381,0.0003031584,0.01123805,0.05408887,0.001692462,0.002855379,0.0000395155],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910289,0.001406989,0.006015922,0.000120327,0.000009857553,0.00004658628,0.0001122012,0.00002776093,0.001231502],"genre_scores_gemma":[0.9959466,0.0005602004,0.002667128,0.00003965698,0.0000242202,0.00004077957,0.00008965463,0.000009220503,0.000622446],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001349944,"threshold_uncertainty_score":0.0036816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0887479737199622,"score_gpt":0.3573920965838414,"score_spread":0.2686441228638792,"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."}}