{"id":"W3118926271","doi":"10.22215/etd/2010-08874","title":"Quantitative fire risk analysis case study using CUrisk","year":2010,"lang":"en","type":"dissertation","venue":"","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Library and Archives Canada","funders":"","keywords":"Humanities; Political science; Art","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":[0.0002206004,0.0003270559,0.0005562639,0.0004687287,0.0001964757,0.000074408,0.0001008074,0.0003539991,0.0003422165],"category_scores_gemma":[0.00003446171,0.0003122156,0.0003026047,0.0009135109,0.000007914256,0.00009209644,0.00000639617,0.0007088649,0.00006963759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006452333,"about_ca_system_score_gemma":0.00002046791,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0155803,"about_ca_topic_score_gemma":0.1090592,"domain_scores_codex":[0.9987092,0.00008877915,0.0004748026,0.0003103429,0.0002264363,0.0001904356],"domain_scores_gemma":[0.9991878,0.00007391664,0.0001487165,0.0003825967,0.0001229879,0.00008395603],"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":[0.0004513618,0.001419633,0.04478131,0.002131378,0.0733159,0.01375976,0.2385517,0.5378278,0.004716655,0.0001293735,0.002376485,0.08053862],"study_design_scores_gemma":[0.000289939,0.000101005,0.002968997,0.00002041807,0.003439164,0.0001197994,0.1008439,0.8910711,0.0001818002,0.000005060267,0.000348803,0.0006099917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923196,0.0002331422,0.001490402,4.837553e-7,0.002002475,0.0004424315,0.00005112122,0.0004121505,0.003048238],"genre_scores_gemma":[0.9968674,0.00003380796,0.0005146471,0.000001482344,0.00008308489,0.00003110231,0.0001309811,0.00006910735,0.002268426],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3532433,"threshold_uncertainty_score":0.999933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01825067684320687,"score_gpt":0.2972910357112615,"score_spread":0.2790403588680547,"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."}}