{"id":"W2338467621","doi":"10.1038/srep20612","title":"Individual Differences in Rhythmic Cortical Entrainment Correlate with Predictive Behavior in Sensorimotor Synchronization","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Neuroscience and Music Perception","field":"Neuroscience","cited_by":772,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; International Laboratory for Brain, Music and Sound Research","funders":"Australian Research Council; Max-Planck-Institut für Kognitions- und Neurowissenschaften; Fonds De La Recherche Scientifique - FNRS","keywords":"Entrainment (biomusicology); Rhythm; Neuroscience; Sensorimotor cortex; Synchronization (alternating current); Computer science; Physical medicine and rehabilitation; Medicine; Biology; Internal 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004035216,0.0002010772,0.0001846345,0.0003648891,0.00006887437,0.000295185,0.0001035648,0.0001692451,0.001325155],"category_scores_gemma":[0.003500751,0.0001157747,0.000102769,0.0002171526,0.0002630141,0.0001679041,0.0002862724,0.0002267623,0.0001553828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006539881,"about_ca_system_score_gemma":0.00007735421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003225465,"about_ca_topic_score_gemma":0.0006250637,"domain_scores_codex":[0.999835,0.00002913859,0.00001885943,0.00005824609,0.00004253904,0.00001613539],"domain_scores_gemma":[0.9984745,0.0005530861,0.0005279366,0.0002870177,0.00007343859,0.00008402706],"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":[0.0009480891,0.0002333894,0.2069667,0.0001201326,0.0003297973,0.0002077266,0.0007321551,0.002139127,0.7440109,0.0005226487,0.0002490873,0.0435402],"study_design_scores_gemma":[0.000004578219,0.0001249413,0.9921124,0.000002553154,0.00001898944,0.0001100013,0.0000284607,0.0009923247,0.006296235,0.0002124474,0.00009150624,0.000005489913],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966173,0.00005929341,0.002313655,0.00001406535,0.00000527651,0.00001792824,0.0001121516,0.00002407098,0.0008364391],"genre_scores_gemma":[0.9989427,0.00003508283,0.0006357399,0.00000931008,0.000003322443,0.00001177,0.00009886272,0.00001207033,0.0002511552],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001325155,"threshold_uncertainty_score":0.004433095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02642768801507556,"score_gpt":0.25132607117822,"score_spread":0.2248983831631445,"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."}}