{"id":"W3210995614","doi":"10.1049/elp2.12135","title":"Design parameters of a reluctance actuation system for stable operation conditions with applications of high‐precision motions in lithography machines","year":2021,"lang":"en","type":"article","venue":"IET Electric Power Applications","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Memorial University of Newfoundland","keywords":"Lithography; Magnetic reluctance; Control engineering; Actuator; Automotive engineering; Control theory (sociology); Engineering; Computer science; Materials science; Mechanical engineering; Electrical engineering; Magnet; Optoelectronics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000529258,0.0006497542,0.0003543936,0.0003500062,0.0003608414,0.0006725335,0.000486991,0.0006579774,0.001852336],"category_scores_gemma":[0.0008443792,0.0002371622,0.0003035956,0.0001692814,0.000358674,0.0003867499,0.0003149582,0.0003176802,0.0003635921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003956382,"about_ca_system_score_gemma":0.0005356097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001642267,"about_ca_topic_score_gemma":0.001396148,"domain_scores_codex":[0.999725,0.00006491136,0.00002363989,0.00006105207,0.00009581116,0.0000295988],"domain_scores_gemma":[0.9995888,0.0001252012,0.0001255296,0.00002624856,0.0001210183,0.00001328445],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004709848,0.0001602804,0.001060004,0.0007881037,0.00008343279,0.0003570371,0.0006394187,0.5231519,0.3703812,0.007121292,0.001075763,0.0947106],"study_design_scores_gemma":[0.00008258,0.0006631663,0.001633763,0.0000466493,0.00004920259,0.0001439242,0.00005842958,0.9557076,0.03746854,0.0009798303,0.003135121,0.00003122699],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1521234,0.0005645602,0.8329342,0.000281588,0.00005833907,0.0002072132,0.00004346321,0.0006742624,0.01311287],"genre_scores_gemma":[0.9804856,0.00006838901,0.01809359,0.00002046685,0.000006032112,0.00008132626,0.00001529911,0.00001217074,0.001217111],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001852336,"threshold_uncertainty_score":0.006196678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006259322387305819,"score_gpt":0.2219656276808669,"score_spread":0.2157063052935611,"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."}}