{"id":"W4311983202","doi":"10.1016/j.psep.2022.11.074","title":"A methodical approach for knowledge-based fire and explosion accident likelihood analysis","year":2022,"lang":"en","type":"article","venue":"Process Safety and Environmental Protection","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University; Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Excellence Research Chairs, Government of Canada; Canada Research Chairs; CRC Health Group; Mary Kay O'Connor Process Safety Center; Genome Canada","keywords":"Process (computing); Accident (philosophy); Hazard; Probabilistic logic; Computer science; Causation; Risk analysis (engineering); Poison control; Domain (mathematical analysis); Database; Engineering; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.007863274,0.001099671,0.00153676,0.003891494,0.001329886,0.004507665,0.003570748,0.001589756,0.005200783],"category_scores_gemma":[0.0351345,0.000758067,0.002689387,0.002723285,0.002715914,0.002737611,0.003773015,0.003041289,0.0008544791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001781049,"about_ca_system_score_gemma":0.003541262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006147545,"about_ca_topic_score_gemma":0.005211207,"domain_scores_codex":[0.9914969,0.004147136,0.0006463847,0.0008965887,0.002577211,0.0002356832],"domain_scores_gemma":[0.9725452,0.02353651,0.0006031657,0.001500948,0.001603551,0.0002105971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001811464,0.0003881376,0.002061997,0.0006461352,0.0005868189,0.0003346268,0.0007446054,0.2275775,0.002726148,0.4094421,0.002978246,0.3523326],"study_design_scores_gemma":[0.00004144222,0.000045825,0.0002848792,0.00007515103,0.00008936721,0.0001401415,0.00008450183,0.5925308,0.001036296,0.4015277,0.004106979,0.00003697997],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003897015,0.00003440063,0.9989797,0.00007281502,0.000007631877,0.00002738089,0.00003136302,0.00005861093,0.0003984135],"genre_scores_gemma":[0.05397976,0.0001541323,0.9442769,0.0001325645,0.00006283434,0.0003599263,0.0001706664,0.00005465513,0.0008085547],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007863274,"threshold_uncertainty_score":0.04158545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05627890645000231,"score_gpt":0.3212813410345765,"score_spread":0.2650024345845742,"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."}}