{"id":"W2900822126","doi":"10.1177/0142331218805138","title":"Modelling and robust position and orientation control of a non-affine nonlinear dielectrophoresis-based micromanipulation system","year":2018,"lang":"en","type":"article","venue":"Transactions of the Institute of Measurement and Control","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Dielectrophoresis; Control theory (sociology); Nonlinear system; Controller (irrigation); Position (finance); Orientation (vector space); Computer science; Engineering; Control engineering; Artificial intelligence; Materials science; Physics; Control (management); Mathematics; Microfluidics; Nanotechnology","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":[0.0004512491,0.0008184151,0.000774909,0.0002935309,0.000497077,0.001189863,0.0007833731,0.0008894412,0.0009978],"category_scores_gemma":[0.0006652292,0.0003701842,0.0005812146,0.000251365,0.0008343494,0.0005065309,0.0009618875,0.0006085876,0.0003064098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005780617,"about_ca_system_score_gemma":0.0009118523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01032498,"about_ca_topic_score_gemma":0.003990085,"domain_scores_codex":[0.9996251,0.00005892496,0.00002585685,0.0001158975,0.0001282863,0.00004591086],"domain_scores_gemma":[0.9997061,0.00006729114,0.0001049404,0.00002761312,0.00007948853,0.00001450952],"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":[0.00006737324,0.00002239663,0.0004350759,0.00009567435,0.00002842484,0.0001484219,0.0001240067,0.9661004,0.01694563,0.005155268,0.0001994553,0.01067799],"study_design_scores_gemma":[0.000008200755,0.00005157284,0.0002056994,0.000004739611,0.000009617195,0.00001741574,0.000008069242,0.9974782,0.001441089,0.0003413244,0.0004274338,0.000006574001],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05335333,0.0004130738,0.9372048,0.0001863225,0.00006750933,0.00007523989,0.00008672314,0.0005446465,0.008068471],"genre_scores_gemma":[0.9802135,0.0003433729,0.01529251,0.00002920938,0.00001843777,0.0001442111,0.00007601203,0.00001842662,0.003864352],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01032498,"threshold_uncertainty_score":0.02052975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01557836223618961,"score_gpt":0.1832132063564905,"score_spread":0.1676348441203009,"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."}}