{"id":"W2809793459","doi":"10.1007/978-3-319-94589-7_16","title":"Expert Elicitation Methodology in the Risk Analysis of an Industrial Machine","year":2018,"lang":"en","type":"book-chapter","venue":"Advances in intelligent systems and computing","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Expert elicitation; Supervisor; Computer science; Judgement; Failure rate; Set (abstract data type); Reliability (semiconductor); Process (computing); Human error; Risk analysis (engineering); Operations research; Artificial intelligence; Reliability engineering; Engineering; Statistics; Mathematics","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":[0.006862107,0.001030276,0.0006998436,0.001636537,0.0005776855,0.001957245,0.001903919,0.00130652,0.004632378],"category_scores_gemma":[0.01318033,0.0004958872,0.0008243957,0.001849456,0.00123004,0.002059433,0.001517839,0.001795528,0.001214594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001453192,"about_ca_system_score_gemma":0.001527283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001462882,"about_ca_topic_score_gemma":0.002277835,"domain_scores_codex":[0.9945416,0.003006733,0.0002925951,0.0004302366,0.001605165,0.0001236927],"domain_scores_gemma":[0.9876416,0.0101887,0.0002832592,0.0006549006,0.001142058,0.00008948058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001428747,0.0002491575,0.001158539,0.001353683,0.0001459316,0.0003783175,0.002467799,0.07091377,0.009139952,0.2854103,0.01121347,0.6174263],"study_design_scores_gemma":[0.00003150498,0.0001780791,0.001491604,0.0007658238,0.0001112492,0.0005628137,0.0006610413,0.334738,0.01419747,0.5846656,0.06250905,0.00008769422],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004412582,0.0009368907,0.9834224,0.000377084,0.00003062773,0.00009116505,0.00008252894,0.0001447125,0.01050205],"genre_scores_gemma":[0.1294017,0.001904844,0.853579,0.0003119532,0.0000880032,0.000287455,0.0003356099,0.0001433516,0.01394804],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006862107,"threshold_uncertainty_score":0.03629071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2535001467966326,"score_gpt":0.445615514187176,"score_spread":0.1921153673905434,"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."}}