{"id":"W2903031638","doi":"10.22215/etd/2016-11397","title":"Development of Multifarious Cueing Systems for Cost-Effective Flight Simulation Training Devices","year":2016,"lang":"en","type":"dissertation","venue":"","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Flight training; Flight simulator; Engineering; Simulation; Training system; Systems engineering; Human–computer interaction; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006403719,0.0004813727,0.0003011028,0.0005741378,0.0002694851,0.0006932413,0.001305513,0.0004949584,0.004883146],"category_scores_gemma":[0.001482661,0.0003205613,0.0002976771,0.0003078003,0.0001690688,0.0009013094,0.0008782299,0.0005250871,0.0006859067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005068164,"about_ca_system_score_gemma":0.0006052298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000797594,"about_ca_topic_score_gemma":0.001552371,"domain_scores_codex":[0.9995404,0.0000497198,0.00003355987,0.00009398555,0.0002312687,0.00005099843],"domain_scores_gemma":[0.9993826,0.0001419851,0.00007720118,0.00005818293,0.0002714966,0.00006852932],"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":[0.0004033249,0.0003933275,0.001867761,0.000478814,0.00003556173,0.0001621237,0.0003366677,0.007289642,0.6208556,0.003932767,0.003600144,0.3606443],"study_design_scores_gemma":[0.0002800296,0.004518875,0.01090256,0.000184906,0.0001682717,0.0009170229,0.0004080819,0.08983407,0.8002603,0.001329118,0.09100772,0.0001890301],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.287992,0.001625862,0.6909831,0.0007174291,0.0004803788,0.001262887,0.000475058,0.002997225,0.01346612],"genre_scores_gemma":[0.3351715,0.000683194,0.6545126,0.0002163366,0.00004980693,0.0004518706,0.0002847115,0.0002111334,0.008418783],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004883146,"threshold_uncertainty_score":0.01633573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02039471325761673,"score_gpt":0.282707138147324,"score_spread":0.2623124248897073,"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."}}