{"id":"W2089346978","doi":"10.1016/j.firesaf.2011.12.007","title":"Modeling the risk of structural fire incidents using a self-organizing map","year":2012,"lang":"en","type":"article","venue":"Fire Safety Journal","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University; York University","funders":"","keywords":"Damages; Risk assessment; Poison control; Sample (material); Forensic engineering; Computer science; Engineering; Computer security; Medical emergency; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.000706524,0.0001912347,0.0002452483,0.00005536039,0.0005175119,0.00004980677,0.000233094,0.0001114218,0.0001004582],"category_scores_gemma":[0.00004952007,0.0001388276,0.0001679321,0.0002047152,0.00001819807,0.0004118832,0.00004904703,0.0006335239,0.00002318084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002299814,"about_ca_system_score_gemma":0.00003036721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001322987,"about_ca_topic_score_gemma":0.0000123197,"domain_scores_codex":[0.9984358,0.0001316211,0.0005978858,0.0000855776,0.0003480906,0.0004010086],"domain_scores_gemma":[0.9993371,0.0000479654,0.0001601943,0.0002104866,0.00009443599,0.0001498443],"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":[0.00004821168,0.00001987191,0.03145995,0.0001550519,0.0005194666,0.000007542756,0.01295586,0.9404167,0.002288525,0.00002501729,0.0002663999,0.01183742],"study_design_scores_gemma":[0.0003206175,0.0000121617,0.007596008,0.0001064178,0.00007213449,0.0007266979,0.0008455208,0.9891284,0.000176345,0.00003835386,0.0008009021,0.0001764929],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9839729,0.002659893,0.01021323,0.00004239322,0.002745729,0.0001156456,0.00001506074,0.0001319943,0.0001031512],"genre_scores_gemma":[0.9974353,0.0001872948,0.001319617,0.00001530764,0.0009759974,8.994063e-7,0.0000016037,0.00004773651,0.00001623795],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04871166,"threshold_uncertainty_score":0.5661225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01220779026090694,"score_gpt":0.2186459833553724,"score_spread":0.2064381930944655,"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."}}