{"id":"W2165919804","doi":"10.3389/fncom.2013.00083","title":"Motor cortical regulation of sparse synergies provides a framework for the flexible control of precision walking","year":2013,"lang":"en","type":"article","venue":"Frontiers in Computational Neuroscience","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Canadian Institutes of Health Research","keywords":"Computer science; Control (management); Motor control; Front (military); Neuroscience; Psychology; Artificial intelligence; Geology","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":[0.0002508931,0.0003100109,0.000340981,0.000433947,0.0001754869,0.0005969805,0.0003297692,0.0002515235,0.001240895],"category_scores_gemma":[0.0007777724,0.0002495345,0.0003277436,0.0002068908,0.0005097988,0.0005427558,0.0007611397,0.0003445713,0.000169862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002484107,"about_ca_system_score_gemma":0.0003680121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001005016,"about_ca_topic_score_gemma":0.001728758,"domain_scores_codex":[0.9998456,0.00001810806,0.00001198851,0.00004083425,0.00004447285,0.00003890101],"domain_scores_gemma":[0.9997621,0.000063466,0.00005378482,0.00004892902,0.00003161192,0.00004017826],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001366207,0.00003788273,0.002448823,0.00009085455,0.00003864154,0.0001865432,0.0001005447,0.004416835,0.9679676,0.00179787,0.0001001304,0.02267762],"study_design_scores_gemma":[0.0001479406,0.001777797,0.6644895,0.0001162967,0.0001563668,0.001187874,0.0003499225,0.1163621,0.1875595,0.02338359,0.004354043,0.0001150872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8692908,0.0006542014,0.1241226,0.0001695059,0.00003119812,0.00009344573,0.0002311093,0.000366846,0.005040106],"genre_scores_gemma":[0.9882608,0.0002005046,0.0106995,0.00003076735,0.00001281211,0.00004659895,0.0000867432,0.00002588379,0.0006364366],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001240895,"threshold_uncertainty_score":0.004151225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02976760234409924,"score_gpt":0.2686810717951977,"score_spread":0.2389134694510985,"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."}}