{"id":"W4386712343","doi":"10.1007/978-3-031-40953-0_35","title":"Can Large Language Models Assist in Hazard Analysis?","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Topic Modeling","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Hazard; Context (archaeology); Session (web analytics); Hazard analysis; Variety (cybernetics); Risk analysis (engineering); Computer security; Artificial intelligence; World Wide Web; Reliability engineering; Engineering; Ecology; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001241521,0.000511697,0.0007812025,0.002555929,0.000163865,0.000549095,0.003942805,0.000347937,0.00001355801],"category_scores_gemma":[0.00007379016,0.0004952686,0.000242233,0.002526161,0.0002115253,0.0005220146,0.001977248,0.0009831639,0.00003703621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004288201,"about_ca_system_score_gemma":0.0005112378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002224606,"about_ca_topic_score_gemma":0.00873057,"domain_scores_codex":[0.9951217,0.00005282842,0.0006592246,0.002008544,0.00119266,0.000965051],"domain_scores_gemma":[0.9970382,0.0003275676,0.0002355175,0.002087628,0.0001264562,0.0001846289],"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":[0.000002351794,0.0000311693,0.0006240809,0.00003354184,0.0000556222,0.0006698731,0.003741208,0.7415388,0.00001843627,0.09389719,0.000008888952,0.1593788],"study_design_scores_gemma":[0.0001762183,0.00002169685,0.00030976,0.0001294136,0.00001922483,0.00001028264,6.446823e-7,0.8544074,0.00005064066,0.1443781,0.00003902387,0.0004576119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003863309,0.0002166151,0.994141,0.001267411,0.001001093,0.0002623161,0.00001631914,0.0002784611,0.002430418],"genre_scores_gemma":[0.7891895,0.00002402695,0.2078813,0.001193063,0.0003082674,0.0000150428,0.00001673181,0.00004806541,0.001323965],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7888032,"threshold_uncertainty_score":0.9997499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02489166734725026,"score_gpt":0.2631933300556764,"score_spread":0.2383016627084261,"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."}}