{"id":"W4242891668","doi":"10.32920/ryerson.14656593","title":"Adaptive PD Sliding Mode Control For 4 DOF SCARA Variant","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"SCARA; Control theory (sociology); Controller (irrigation); Trajectory; Adaptive control; Computer science; A priori and a posteriori; Tracking (education); Control engineering; Robot; Engineering; Control (management); Artificial intelligence; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001755988,0.0003384417,0.0005119978,0.00007578124,0.00005508376,0.0001509352,0.0002999064,0.0003156364,0.0002305793],"category_scores_gemma":[0.00003509531,0.0003224592,0.0002716176,0.00005321311,0.00001194003,0.00006523579,0.0001436322,0.000421131,0.0000150566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001149713,"about_ca_system_score_gemma":0.0000637748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001860463,"about_ca_topic_score_gemma":0.00006630508,"domain_scores_codex":[0.9986235,0.00002483073,0.0003628787,0.0004556289,0.0001701085,0.0003630275],"domain_scores_gemma":[0.9990969,0.0001073591,0.00004802989,0.0005008592,0.0001450082,0.0001018117],"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":[0.00001499226,0.00001585785,0.000003893564,0.0002088057,0.0003033285,0.00002567044,0.0003187315,0.981716,0.0009176249,0.0115575,0.000658564,0.004259017],"study_design_scores_gemma":[0.0002118326,0.00001963737,0.00001316888,0.0001619111,0.00007328601,0.000008659304,0.0001572317,0.9903344,0.006361128,0.001778051,0.0004645615,0.0004161537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001983985,0.0009155548,0.9878881,0.00005812262,0.00141108,0.0006963054,0.0000965255,0.0003072713,0.006643042],"genre_scores_gemma":[0.9630295,0.0001771939,0.03550829,0.00008212106,0.0002867829,0.0002547924,0.0000553294,0.00007514283,0.0005308539],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9610455,"threshold_uncertainty_score":0.9999228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02936197239656936,"score_gpt":0.2518421676335879,"score_spread":0.2224801952370185,"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."}}