{"id":"W4386332795","doi":"10.3390/aerospace10090770","title":"Examining the Potential of Generative Language Models for Aviation Safety Analysis: Case Study and Insights Using the Aviation Safety Reporting System (ASRS)","year":2023,"lang":"en","type":"article","venue":"Aerospace","topic":"Topic Modeling","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"General Fusion (Canada)","funders":"","keywords":"Aviation; Aviation safety; Computer science; Context (archaeology); Process (computing); Generative grammar; Risk analysis (engineering); Engineering; Artificial intelligence; Business","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":[0.01151895,0.001345643,0.0004663901,0.002531924,0.00077078,0.002922602,0.001529905,0.001568481,0.001495421],"category_scores_gemma":[0.04840725,0.0004669767,0.001380075,0.001527124,0.00138697,0.003344219,0.002413516,0.001904405,0.000624848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001837806,"about_ca_system_score_gemma":0.001686317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008008091,"about_ca_topic_score_gemma":0.01119541,"domain_scores_codex":[0.9880497,0.009542285,0.0003572811,0.0009233154,0.0009185473,0.0002088683],"domain_scores_gemma":[0.9304671,0.0617543,0.001740434,0.003444093,0.002152706,0.0004412905],"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":[0.001864445,0.001663089,0.0974161,0.002997407,0.0006192999,0.004243536,0.03239468,0.4647644,0.01876221,0.04242279,0.01297752,0.3198746],"study_design_scores_gemma":[0.00009403002,0.0005650721,0.007267291,0.0003677563,0.0001542868,0.0007713002,0.005598604,0.9401462,0.008687151,0.0211398,0.01507378,0.0001348036],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6059676,0.001427848,0.3743319,0.004074575,0.0002148134,0.0008305702,0.002719868,0.003686068,0.006746795],"genre_scores_gemma":[0.79527,0.0003700608,0.1987395,0.0004012967,0.00005183959,0.0003889393,0.003290974,0.000318839,0.001168609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01151895,"threshold_uncertainty_score":0.06091881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06448011856139108,"score_gpt":0.3037445477884083,"score_spread":0.2392644292270172,"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."}}