{"id":"W2004879035","doi":"10.1017/s0263574713000775","title":"Function approximation technique-based adaptive virtual decomposition control for a serial-chain manipulator","year":2013,"lang":"en","type":"article","venue":"Robotica","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Space Agency","funders":"","keywords":"Representation (politics); Serial manipulator; Computer science; Control theory (sociology); Controller (irrigation); Stability (learning theory); MATLAB; Decomposition; Adaptive control; Function approximation; Robot; Function (biology); Matrix (chemical analysis); Control engineering; Control (management); Artificial intelligence; Artificial neural network; Parallel manipulator; Engineering; Machine learning","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":[0.0004383451,0.0003985323,0.0002946721,0.0002512268,0.0002645655,0.0003604686,0.0003543088,0.0003056236,0.001138245],"category_scores_gemma":[0.0004114314,0.0001319863,0.0003199186,0.0002252561,0.0003293815,0.0001746932,0.000344324,0.0003013038,0.0001499662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002949369,"about_ca_system_score_gemma":0.0004146184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004040489,"about_ca_topic_score_gemma":0.001884002,"domain_scores_codex":[0.9998763,0.00003195399,0.000007131423,0.00002316477,0.00004652818,0.00001499416],"domain_scores_gemma":[0.9998474,0.00004047491,0.00003647162,0.00001630709,0.00005165369,0.000007755583],"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":[0.0001108394,0.00004050948,0.0004052647,0.00008218914,0.0000224895,0.0001019767,0.00007592211,0.9200028,0.02990201,0.006206128,0.0004310303,0.04261882],"study_design_scores_gemma":[0.000005547878,0.00005038211,0.00008929442,0.000002794827,0.000003075079,0.000009467511,0.000002615107,0.9983636,0.0009618988,0.0002715366,0.0002374977,0.000002478908],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05623373,0.0001035412,0.9402772,0.00007256701,0.00003157473,0.00002989287,0.00001480928,0.0002656478,0.00297099],"genre_scores_gemma":[0.9436643,0.00009202599,0.05374009,0.00002266801,0.00001035916,0.00006498158,0.00002862391,0.00001465843,0.002362205],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004040489,"threshold_uncertainty_score":0.008033931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00919306763325773,"score_gpt":0.2038591838813482,"score_spread":0.1946661162480905,"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."}}