{"id":"W1980510435","doi":"10.1016/j.ics.2005.12.027","title":"Learning the dynamics of the external world: Brain inspired learning for robotic applications","year":2006,"lang":"en","type":"article","venue":"International Congress Series","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"National Institute of Information and Communications Technology","keywords":"Dynamics (music); Artificial intelligence; Computer science; Mechanical impedance; Adaptation (eye); Robotics; Human–computer interaction; Field (mathematics); Cognitive science; Robot; Neuroscience; Psychology; Engineering; Electrical impedance","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":[0.00022548,0.0002394603,0.0002168379,0.0001417039,0.0001022502,0.0007208164,0.0002577996,0.0004844231,0.002161806],"category_scores_gemma":[0.001013352,0.0001046777,0.0001645086,0.0002154297,0.0004776744,0.0007609149,0.0002662443,0.0006322249,0.0003049312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001352301,"about_ca_system_score_gemma":0.0001590526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004495587,"about_ca_topic_score_gemma":0.0005555591,"domain_scores_codex":[0.9999694,0.000006325843,0.000001872458,0.000008565412,0.000009695412,0.000004183408],"domain_scores_gemma":[0.9998989,0.00005872241,0.00001050261,0.00001088397,0.00001281619,0.00000806217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002023468,0.0001369503,0.00176781,0.0003930125,0.0001240531,0.0001875574,0.0002359669,0.1392958,0.0870304,0.04387557,0.006083014,0.7206674],"study_design_scores_gemma":[0.00005881123,0.0004080284,0.005967181,0.000109857,0.00008279654,0.0004801842,0.000160447,0.7774991,0.04422951,0.1417507,0.02919352,0.00005982568],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1728951,0.01323482,0.7870162,0.003399702,0.0005585204,0.00006146912,0.0001076935,0.0004458652,0.02228062],"genre_scores_gemma":[0.8622844,0.009100639,0.1155462,0.0002488584,0.000231129,0.00007593241,0.0001026107,0.00007407998,0.01233602],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002161806,"threshold_uncertainty_score":0.007231951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006813931257073711,"score_gpt":0.2273981874128828,"score_spread":0.2205842561558091,"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."}}