{"id":"W3127612924","doi":"10.1101/2021.02.09.430495","title":"Motor Sequences - Separating The Sequence From The Motor. A longitudinal rsfMRI Study","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Concordia University; Montreal Neurological Institute and Hospital; Montreal Heart Institute","funders":"Max-Planck-Institut für demografische Forschung; Max-Planck-Gesellschaft; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Heart and Stroke Foundation of Canada","keywords":"Sequence learning; Motor learning; Serial reaction time; Supplementary motor area; Primary motor cortex; Sequence (biology); SMA*; Task (project management); Motor cortex; Neuroscience; Functional connectivity; Psychology; Resting state fMRI; Functional magnetic resonance imaging; Computer science; Cognitive psychology; Biology","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":[0.0007495539,0.0002834185,0.0002398423,0.0003500046,0.0002796481,0.0003061135,0.0002018658,0.000412853,0.001458185],"category_scores_gemma":[0.0007911515,0.0001758773,0.0001822142,0.0001699782,0.0004311699,0.0004824768,0.0002867816,0.000502869,0.000462981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002170695,"about_ca_system_score_gemma":0.0002905271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001533938,"about_ca_topic_score_gemma":0.00440459,"domain_scores_codex":[0.999837,0.00002394278,0.00001048507,0.00008250956,0.00002466443,0.00002135457],"domain_scores_gemma":[0.9994982,0.00003950361,0.0002356834,0.00006441807,0.00006547108,0.00009674745],"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":[0.003781311,0.004545588,0.4309141,0.0003519883,0.0004310057,0.00118212,0.001627924,0.00123004,0.4535542,0.0007925548,0.001331183,0.100258],"study_design_scores_gemma":[0.00003597593,0.004144166,0.9796739,0.00002914665,0.00009381755,0.0009810836,0.0001884675,0.001074238,0.01146463,0.0004528663,0.001842402,0.00001922576],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997718,0.0004234732,0.001097203,0.00004970673,0.000008937272,0.00003532465,0.0001426987,0.00001321546,0.000511384],"genre_scores_gemma":[0.9969144,0.0001927466,0.0008442075,0.00004127614,0.00001198942,0.00004485378,0.0003488735,0.000009481244,0.001592208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001533938,"threshold_uncertainty_score":0.004878163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06482268616797103,"score_gpt":0.2759768495004417,"score_spread":0.2111541633324706,"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."}}