{"id":"W2075436524","doi":"10.1080/10798587.2014.901651","title":"Emotional Learning Based Position Control of Pneumatic Actuators","year":2014,"lang":"en","type":"article","venue":"Intelligent Automation & Soft Computing","topic":"Hydraulic and Pneumatic Systems","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Actuator; Position (finance); Control (management); Pneumatic actuator; Position paper; Artificial intelligence","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":[0.0002779642,0.0003441722,0.0002451254,0.0001522682,0.0003028238,0.0004369196,0.0006647051,0.0003353973,0.00122341],"category_scores_gemma":[0.0006800671,0.0001186453,0.0002075583,0.0001046496,0.0003610778,0.0004051827,0.0005252125,0.0003859779,0.0002339183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001924718,"about_ca_system_score_gemma":0.0001590966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003776728,"about_ca_topic_score_gemma":0.0004268928,"domain_scores_codex":[0.9997788,0.00003426862,0.00001677958,0.00004941161,0.00009696667,0.00002371107],"domain_scores_gemma":[0.9998072,0.00005041797,0.00004303185,0.00002446504,0.00005651485,0.00001845345],"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":[0.0005500326,0.0002087547,0.001085891,0.0003830074,0.00006009005,0.0003435215,0.0003741001,0.124861,0.3222478,0.01770563,0.001710841,0.5304695],"study_design_scores_gemma":[0.00005159055,0.0006288025,0.001457401,0.00002614063,0.00004482534,0.0002077389,0.00002859207,0.9307562,0.05662721,0.00422983,0.00590829,0.00003327729],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0472114,0.0004747764,0.9450476,0.0001250748,0.0001668662,0.00006954811,0.00001404811,0.0004914959,0.006399129],"genre_scores_gemma":[0.9430135,0.0002002419,0.05327902,0.000120669,0.00006167399,0.00005882684,0.00001699936,0.00002334108,0.003225642],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00122341,"threshold_uncertainty_score":0.004092753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007225334639223004,"score_gpt":0.2116822762034191,"score_spread":0.2044569415641961,"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."}}