{"id":"W4239802080","doi":"10.3410/f.732604736.793560110","title":"Faculty Opinions recommendation of Motor Cortex Embeds Muscle-like Commands in an Untangled Population Response.","year":2019,"lang":"en","type":"dataset","venue":"Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"N. Bud Grossman Center for Memory Research and Care; G. Harold and Leila Y. Mathers Foundation; McKnight Foundation; Kavli Foundation; Burroughs Wellcome Fund; Simons Foundation; Helen Hay Whitney Foundation; Searle Scholars Program; Alfred P. Sloan Foundation; Howard Hughes Medical Institute; National Institutes of Health; National Science Foundation","keywords":"Motor cortex; Neuroscience; Robustness (evolution); Population; Cortex (anatomy); Primary motor cortex; Computer science; Biology; Medicine; Stimulation; Gene","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":[0.001148744,0.001589445,0.000708011,0.001703398,0.0005070401,0.001474264,0.001983005,0.001928738,0.02121171],"category_scores_gemma":[0.006143671,0.0003157426,0.001391761,0.0019679,0.0003932898,0.000737178,0.001076614,0.001192714,0.03775623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001000433,"about_ca_system_score_gemma":0.001265911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01602569,"about_ca_topic_score_gemma":0.0473692,"domain_scores_codex":[0.9993601,0.0001231585,0.00005182376,0.0002703655,0.0001083693,0.0000861052],"domain_scores_gemma":[0.9986921,0.000431128,0.0001613895,0.0003423472,0.0002510323,0.0001219187],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003562775,0.00008944176,0.01421415,0.001588017,0.000309335,0.0001358109,0.00004992899,0.002697796,0.001165906,0.00114093,0.9582497,0.02000273],"study_design_scores_gemma":[0.0005282185,0.0001028493,0.05315114,0.0004841194,0.0002619104,0.0004238899,0.0001253765,0.01259167,0.002952131,0.006146489,0.9231542,0.00007796202],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004510532,0.0008764481,0.001007411,0.0005678942,0.0001950929,0.00003189673,0.9880908,0.00160947,0.003110393],"genre_scores_gemma":[0.01143847,0.0001999534,0.001299623,0.0001432785,0.00004668895,0.00007450549,0.9840648,0.0001138211,0.002618867],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02121171,"threshold_uncertainty_score":0.07096022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04958458877732939,"score_gpt":0.3616944837892446,"score_spread":0.3121098950119152,"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."}}