{"id":"W2903359691","doi":"10.1146/annurev-statistics-031017-100450","title":"Statistical Models of Key Components of Wildfire Risk","year":2018,"lang":"en","type":"article","venue":"Annual Review of Statistics and Its Application","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Natural Resources Canada; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Key (lock); Risk analysis (engineering); Variety (cybernetics); Computer science; Process (computing); Risk management; Management science; Environmental resource management; Data science; Operations research; Engineering; Environmental science; Business; Artificial intelligence; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00302004,0.001101927,0.0008564452,0.001960704,0.0004215854,0.002248523,0.002114338,0.001348116,0.002228414],"category_scores_gemma":[0.0136541,0.0005573791,0.0008771694,0.001860413,0.001504347,0.00377492,0.001145653,0.00231458,0.0006248316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001420307,"about_ca_system_score_gemma":0.001307611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004472866,"about_ca_topic_score_gemma":0.003488342,"domain_scores_codex":[0.998952,0.0003762333,0.00006300887,0.0001965878,0.0003119348,0.0001002357],"domain_scores_gemma":[0.9944537,0.003753359,0.0008543332,0.0003398589,0.0004592114,0.0001394629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001538078,0.00003708212,0.00447822,0.00008425862,0.00009320799,0.00007253903,0.0001708374,0.351631,0.0004137159,0.6215918,0.001769194,0.01964281],"study_design_scores_gemma":[0.000003186139,0.00001971058,0.001502808,0.00003893472,0.00002718408,0.00006841172,0.00003694941,0.6349416,0.0001472525,0.3598471,0.003340507,0.00002635211],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.0482416,0.005037333,0.9308122,0.002615335,0.0001736326,0.00005342508,0.0007477976,0.0003088875,0.01200987],"genre_scores_gemma":[0.9010782,0.01547778,0.06516548,0.0004687836,0.001068448,0.0003054856,0.001436193,0.0002536765,0.014746],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.004472866,"threshold_uncertainty_score":0.01597166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009032840692660797,"score_gpt":0.2576795427386559,"score_spread":0.2486467020459951,"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."}}