{"id":"W1897713772","doi":"10.1111/risa.12313","title":"Development of Economic Consequence Methodology for Process Risk Analysis","year":2014,"lang":"en","type":"article","venue":"Risk Analysis","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Risk analysis (engineering); Process (computing); Identification (biology); Computer science; Function (biology); Risk assessment; Reliability engineering; Operations research; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01923639,0.0003139483,0.00228402,0.003499747,0.0005357268,0.0001147448,0.001387079,0.0001911058,0.001234967],"category_scores_gemma":[0.007216291,0.0002392628,0.002396246,0.007928893,0.0002759314,0.0002164583,0.000113736,0.0001848738,0.0001457458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009637825,"about_ca_system_score_gemma":0.0002591558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009898754,"about_ca_topic_score_gemma":0.01230031,"domain_scores_codex":[0.9933588,0.001703805,0.002348816,0.001214064,0.0009084263,0.0004660686],"domain_scores_gemma":[0.9872825,0.007720559,0.002580442,0.001446701,0.0007458254,0.0002239948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001285091,0.00007145627,0.4424364,0.000007251121,0.02314711,9.440097e-7,0.002057191,0.3459716,0.00008988365,0.0008415905,0.0001281439,0.18512],"study_design_scores_gemma":[0.0005824993,0.00006168673,0.101105,0.000003160816,0.05244491,0.000001117558,0.002311955,0.7559242,0.003925731,0.07733253,0.005723875,0.0005833403],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.460063,0.0001017802,0.5391918,0.0001100134,0.00003915,0.00009462816,0.0001103489,0.00001904655,0.0002702289],"genre_scores_gemma":[0.8240089,0.0002637947,0.1752184,0.00003117016,0.0000419615,0.0000431984,0.00004891003,0.00001084423,0.0003327943],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4099527,"threshold_uncertainty_score":0.999678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1595662560432212,"score_gpt":0.4490968715265901,"score_spread":0.2895306154833689,"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."}}