{"id":"W2438122347","doi":"","title":"An integrated approach for assessing human health risk in process facility","year":2009,"lang":"en","type":"dissertation","venue":"Memorial University Research Repository (Memorial University)","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Risk analysis (engineering); Risk assessment; Probabilistic risk assessment; Probabilistic logic; Process (computing); Hazard; Risk management; Human health; Hazard analysis; Bayesian network; Human error; Computer science; Engineering; Reliability engineering; Environmental health; Business; Medicine; Machine learning; Computer security; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001794455,0.0009603987,0.000691106,0.002023099,0.0005589369,0.002104069,0.001366303,0.001113522,0.003015077],"category_scores_gemma":[0.002312057,0.0003733789,0.001364385,0.00101926,0.0005731169,0.001566191,0.001767374,0.0009479338,0.0004324657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001724222,"about_ca_system_score_gemma":0.002166856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005405026,"about_ca_topic_score_gemma":0.00452722,"domain_scores_codex":[0.9981187,0.0006113928,0.00008547706,0.0002488121,0.0008378439,0.0000977371],"domain_scores_gemma":[0.9991857,0.0002890575,0.0001096428,0.00005246331,0.0003313365,0.00003161727],"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":[0.00009376535,0.0003034655,0.009385679,0.000685059,0.0003685665,0.0003631737,0.0006917781,0.6176113,0.01573784,0.1078101,0.002809892,0.2441394],"study_design_scores_gemma":[0.00001660462,0.0004184719,0.004444229,0.0002002144,0.0002323873,0.0002877537,0.0005947351,0.8993342,0.00575427,0.07419676,0.01443978,0.00008061963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01634217,0.0006890242,0.9675319,0.0003732987,0.00004069917,0.0002744511,0.0001785983,0.0002288893,0.01434113],"genre_scores_gemma":[0.4363759,0.001597396,0.5494148,0.0001997571,0.00006104965,0.0007826459,0.0003529868,0.00007058137,0.011145],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005405026,"threshold_uncertainty_score":0.01251018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0970019292225253,"score_gpt":0.4042009048252585,"score_spread":0.3071989756027332,"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."}}