{"id":"W4413630458","doi":"10.1109/access.2025.3602259","title":"A Machine Learning Framework for Fire Risk Prediction With Response and Proximity Insights","year":2025,"lang":"en","type":"article","venue":"IEEE Access","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Telus (Canada); Alberta Health Services; Ontario Tech University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Machine learning; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001662357,0.000099591,0.0001218895,0.00007955576,0.0001699541,0.00008678366,0.0000764222,0.0001004899,0.000003086562],"category_scores_gemma":[0.0001185509,0.00008275822,0.000022111,0.0002235743,0.00001703361,0.0002320405,0.0000116925,0.0002430712,0.000001335255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003595629,"about_ca_system_score_gemma":0.00001249073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004935907,"about_ca_topic_score_gemma":0.0000458284,"domain_scores_codex":[0.9994791,0.0000623357,0.000135121,0.0001466348,0.00006841253,0.0001084623],"domain_scores_gemma":[0.9995578,0.0002202909,0.00003244765,0.0001214932,0.00003392778,0.00003402649],"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":[0.0147993,0.000189256,0.268423,0.003689309,0.00129098,0.00003276878,0.008523612,0.4867473,0.006020369,0.001957862,0.00474218,0.2035841],"study_design_scores_gemma":[0.000988665,0.0001877908,0.07913393,0.0003270921,0.00005036919,0.000008431593,0.00006303888,0.8801814,0.003567713,0.001338671,0.03394555,0.0002073455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7698647,0.0004359969,0.2281037,0.00006528128,0.0005496866,0.0003637246,0.00001693034,0.0003801202,0.0002198646],"genre_scores_gemma":[0.9989443,0.00009394941,0.0004445742,0.00002512062,0.00006646572,0.0001101805,0.000003063553,0.00001707111,0.0002952894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3934341,"threshold_uncertainty_score":0.3374782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009608752485894536,"score_gpt":0.2442075188199485,"score_spread":0.2345987663340539,"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."}}