{"id":"W3130374006","doi":"10.20338/bjmb.v14i5.211","title":"Shared internal models between feedforward and feedback control","year":2020,"lang":"en","type":"article","venue":"Brazilian Journal of Motor Behavior","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Canada Research Chairs","keywords":"Feed forward; Internal model; Control (management); Computer science; Feedback control; Control theory (sociology); Control engineering; Engineering; Artificial intelligence","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":[0.000987783,0.0006299447,0.001059902,0.0002956102,0.0004142721,0.001743415,0.001142349,0.001201345,0.003920633],"category_scores_gemma":[0.003168844,0.0004672948,0.0008665328,0.0002756345,0.001125427,0.002640164,0.002107231,0.001150439,0.0004970183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005936773,"about_ca_system_score_gemma":0.0009045791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002035874,"about_ca_topic_score_gemma":0.001766769,"domain_scores_codex":[0.9993398,0.0002181447,0.00003387527,0.0001349767,0.0001916195,0.00008167448],"domain_scores_gemma":[0.9988668,0.0004592837,0.0001127551,0.0002491955,0.0002474046,0.00006453191],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001403765,0.00008012764,0.0006098624,0.0001176957,0.0001121669,0.0001452401,0.0002818371,0.7511922,0.00350422,0.2047688,0.0007757237,0.03827185],"study_design_scores_gemma":[0.0000123576,0.00006524024,0.0002896135,0.00001527509,0.00002197443,0.00002433754,0.00002890871,0.9407901,0.0006681785,0.05754033,0.0005312101,0.00001241223],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04042297,0.0002243484,0.9494438,0.0003452515,0.00009015801,0.000020375,0.00005744668,0.0001655639,0.009230079],"genre_scores_gemma":[0.9716035,0.0001037474,0.02286668,0.00004847537,0.00002989176,0.00005354028,0.00006101077,0.00004343431,0.005189562],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003920633,"threshold_uncertainty_score":0.01311588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01642161670845097,"score_gpt":0.2227720359500068,"score_spread":0.2063504192415558,"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."}}