{"id":"W4238206108","doi":"10.32920/ryerson.14648895","title":"Enhancing the functional design of a multi-touch UAV ground control station","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Simulation and Modeling Applications","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Interface (matter); Gesture; Key (lock); Fidelity; Remote control; Simulation; Control (management); Computer science; Virtual reality; High fidelity; Human–computer interaction; Engineering; Computer hardware; Computer vision; Artificial intelligence; Telecommunications; Electrical engineering; Operating system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002362187,0.0005461325,0.0002163979,0.0002566526,0.0002530331,0.0008077938,0.001311046,0.0007973725,0.008118394],"category_scores_gemma":[0.0006829613,0.0003432866,0.0003284462,0.0000857159,0.0002610146,0.000592215,0.0006368363,0.0004102382,0.001512295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002145385,"about_ca_system_score_gemma":0.0003145393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007049711,"about_ca_topic_score_gemma":0.000705219,"domain_scores_codex":[0.9996572,0.00005005681,0.00001777291,0.00007387025,0.0001535442,0.00004769749],"domain_scores_gemma":[0.9996989,0.00007801477,0.00003388082,0.00005745771,0.00008710185,0.00004476411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003046159,0.0001650822,0.001959371,0.0004918293,0.00004318312,0.001102673,0.0008131363,0.04807052,0.8111955,0.005128607,0.001621412,0.1291041],"study_design_scores_gemma":[0.0001321835,0.002267564,0.009060981,0.0001261906,0.0001271499,0.001979381,0.000423075,0.4786382,0.4256858,0.001331461,0.08013172,0.00009620054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1811561,0.0001947568,0.7987975,0.0001555875,0.00010871,0.0002322325,0.0001003797,0.003326623,0.01592803],"genre_scores_gemma":[0.8041513,0.0001461586,0.1830133,0.00009913572,0.00002198664,0.00017022,0.0001187222,0.000255884,0.01202321],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008118394,"threshold_uncertainty_score":0.02715874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05826815070242023,"score_gpt":0.2690688799342574,"score_spread":0.2108007292318372,"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."}}