{"id":"W2099101692","doi":"10.1016/j.neuroimage.2008.03.042","title":"Functional neuroanatomical networks associated with expertise in motor imagery","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Sport Psychology and Performance","field":"Psychology","cited_by":313,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre for Interdisciplinary Research in Rehabilitation; Université de Montréal; Université Laval; Canadian Institutes of Health Research; Research Canada","funders":"","keywords":"Neuroscience; Psychology; Functional magnetic resonance imaging; Putamen; Cerebellum; Premotor cortex; Neuropsychology; Motor imagery; Supplementary motor area; Cognitive psychology; Electroencephalography; Cognition; Anatomy; Medicine","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001403514,0.0001914435,0.0002250388,0.0001425558,0.0001178939,0.00000887208,0.0001576803,0.0001730602,0.002368388],"category_scores_gemma":[0.0000413593,0.0001744082,0.00006180824,0.0003500672,0.0002580144,0.0001516562,0.00002349364,0.000635852,0.0003286272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002967625,"about_ca_system_score_gemma":0.0000280828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002544778,"about_ca_topic_score_gemma":0.00001721704,"domain_scores_codex":[0.9984807,0.0001379387,0.0002684028,0.0004995347,0.0001595318,0.0004538767],"domain_scores_gemma":[0.9992934,0.0001205479,0.00008810763,0.0003685567,0.00003518357,0.00009420331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001813243,0.000880397,0.9031311,0.000002301376,0.00004686787,0.005617022,0.0005305794,0.0002196125,0.0008684301,0.0001341066,0.08436615,0.002390207],"study_design_scores_gemma":[0.001593175,0.0001777061,0.9948145,0.000007930658,0.000006425701,0.0004438643,0.00001137424,0.001276928,0.00001975643,0.000007048079,0.001464081,0.0001771831],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9832477,0.0002030835,0.0003430145,0.000255487,0.001142465,0.0001662067,0.000006273203,0.0001346788,0.01450112],"genre_scores_gemma":[0.9919065,0.00002339991,0.00002262518,0.002808535,0.0001947473,0.00006037581,0.00002945235,0.00003906572,0.004915286],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09168344,"threshold_uncertainty_score":0.9985436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03675778727209967,"score_gpt":0.2729581670772773,"score_spread":0.2362003798051777,"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."}}