{"id":"W4406493335","doi":"10.1038/s41598-025-85448-7","title":"Exploring technology acceptance of flight simulation training devices and augmented reality in general aviation pilot training","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"University of Waterloo","keywords":"Aviation; Training (meteorology); Flight training; Augmented reality; General aviation; Computer science; Aeronautics; Flight simulator; Point (geometry); Scale (ratio); Simulation; Human–computer interaction; Engineering; Aerospace engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004104645,0.000256067,0.0001650031,0.000724408,0.000768855,0.001950831,0.0003487054,0.0006346823,0.002070541],"category_scores_gemma":[0.0118439,0.0001896261,0.0002835412,0.0004688748,0.001266464,0.0009992636,0.001488779,0.0006362306,0.000184197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001215295,"about_ca_system_score_gemma":0.001431959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01542228,"about_ca_topic_score_gemma":0.01780687,"domain_scores_codex":[0.9964741,0.001981864,0.000132551,0.0001393371,0.0008793981,0.0003927346],"domain_scores_gemma":[0.9911391,0.005260572,0.001154247,0.0002002077,0.001495198,0.0007506069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005356388,0.0007044091,0.4542819,0.0005528158,0.00007018964,0.002159635,0.4105275,0.0007215842,0.01150308,0.001753849,0.0009715154,0.116218],"study_design_scores_gemma":[0.00003413223,0.002145323,0.4373879,0.0004485675,0.00005620615,0.001717414,0.5410461,0.001915804,0.001771365,0.0003061717,0.01308974,0.00008122109],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967625,0.00009847496,0.0004091268,0.0001762639,0.000004809171,0.00001590341,0.00001097798,0.000003382816,0.002518611],"genre_scores_gemma":[0.9990911,0.0001530032,0.0002964938,0.00004849226,0.000002525634,0.00001461505,0.00001181019,0.000001720602,0.0003801752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01542228,"threshold_uncertainty_score":0.03066504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1486608165237043,"score_gpt":0.3328175284498259,"score_spread":0.1841567119261215,"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."}}