{"id":"W3201304010","doi":"10.1109/mercon52712.2021.9525652","title":"Quadcopter Disturbance Estimation using Different Learning Methods","year":2021,"lang":"en","type":"article","venue":"","topic":"Gaussian Processes and Bayesian Inference","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Quadcopter; Computer science; Artificial neural network; Aerodynamics; Process (computing); Artificial intelligence; Control theory (sociology); Control engineering; System dynamics; Vehicle dynamics; Gaussian process; Machine learning; Engineering; Gaussian; Control (management); Automotive engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001322927,0.0001132034,0.0001387696,0.00003397842,0.0001434473,0.0003247029,0.0002933895,0.00003926607,0.00009979963],"category_scores_gemma":[0.00008797813,0.00008990082,0.00004684933,0.0002821242,0.00001800038,0.0004381027,0.0002080368,0.000134794,0.00002032914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003261986,"about_ca_system_score_gemma":0.00006319282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009252954,"about_ca_topic_score_gemma":0.000002158957,"domain_scores_codex":[0.9990225,0.0001157094,0.0001734291,0.0003366182,0.0001503291,0.0002014357],"domain_scores_gemma":[0.9994072,0.00007836012,0.00006828934,0.0002961801,0.00008548093,0.00006452062],"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":[0.000002417126,0.0001079511,0.004221824,0.000104153,0.00002543431,0.00004314355,0.0007982102,0.005066318,0.01303286,0.2876339,0.00009644398,0.6888674],"study_design_scores_gemma":[0.00009220627,0.00001794019,0.004163957,0.00003581651,0.000005319796,0.00003561147,0.0000265477,0.9453132,0.03577609,0.01378175,0.0005829438,0.0001686144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01148303,0.0001663697,0.9842321,0.0004972813,0.0001966975,0.00003190038,1.290888e-7,0.0001342246,0.003258275],"genre_scores_gemma":[0.4652502,0.000005465296,0.5340166,0.000108487,0.00001521127,0.000002107661,9.824225e-7,0.000003384187,0.0005976019],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9402469,"threshold_uncertainty_score":0.3666049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02730823881639808,"score_gpt":0.3340806802318916,"score_spread":0.3067724414154935,"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."}}