{"id":"W4404471759","doi":"10.1177/17298806241283228","title":"Adaptive iterative learning control for enhancing the dynamic path tracking accuracy of 6-degrees of freedom industrial robots","year":2024,"lang":"en","type":"article","venue":"International Journal of Advanced Robotic Systems","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Iterative learning control; Degrees of freedom (physics and chemistry); Robot; Path (computing); Tracking (education); Artificial intelligence; Control (management); Control theory (sociology); Control engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001059792,0.000241018,0.000683327,0.0003375229,0.00005718645,0.0001522222,0.0004674861,0.0001087529,0.000005797983],"category_scores_gemma":[0.001210172,0.0001742551,0.0003128434,0.0001811513,0.00006634284,0.0006087074,0.00002258537,0.0005949361,0.000001720525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003006671,"about_ca_system_score_gemma":0.0001207264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001954049,"about_ca_topic_score_gemma":0.00001402899,"domain_scores_codex":[0.9972621,0.0002615319,0.0014562,0.0001651012,0.0006326197,0.0002224903],"domain_scores_gemma":[0.9946938,0.003071196,0.0009096371,0.0001186055,0.00115635,0.00005045363],"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":[0.0002035649,0.00001682489,0.0001771628,0.0001312422,0.001118419,0.00002382262,0.002473788,0.9449832,0.04459539,0.001790652,0.00003137658,0.004454538],"study_design_scores_gemma":[0.002113489,0.0004183974,0.0002717171,0.004733123,0.0001095943,0.0001651006,0.002234892,0.988622,0.0007324324,0.00005830071,0.0003721762,0.000168781],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03449598,0.005482261,0.9493675,0.000113578,0.009639662,0.0006974349,0.00003629582,0.0000549707,0.0001123726],"genre_scores_gemma":[0.9970642,0.00003899327,0.001634708,0.000003212174,0.001077198,0.00003029829,0.000005218988,0.00005265861,0.00009348695],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9625682,"threshold_uncertainty_score":0.7105917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.016634457838936,"score_gpt":0.2715835606774903,"score_spread":0.2549491028385543,"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."}}