{"id":"W4408483743","doi":"10.5194/egusphere-egu25-20461","title":"Enhancing Wildfire Resilience: A Comprehensive Approach for the Wildland-Urban Interface and Infrastructure","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Wildland–urban interface; Resilience (materials science); Environmental resource management; Interface (matter); Environmental planning; Business; Critical infrastructure; Environmental science; Computer science; Geography; Computer security; Meteorology; Materials science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001173039,0.001043938,0.0006008742,0.001363922,0.001186084,0.003055575,0.001425619,0.001519743,0.003084042],"category_scores_gemma":[0.001090261,0.0003337684,0.0009124607,0.0007840654,0.00229082,0.003978684,0.003820817,0.001415189,0.0002784334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001397355,"about_ca_system_score_gemma":0.003169656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003103644,"about_ca_topic_score_gemma":0.006643841,"domain_scores_codex":[0.9996055,0.0001239271,0.00001635916,0.00007518308,0.0001061844,0.00007294984],"domain_scores_gemma":[0.9996229,0.00009991195,0.00003902866,0.00007106757,0.00006425038,0.0001026942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004425196,0.0001579331,0.00267892,0.0004449525,0.0001088523,0.0004574058,0.001180666,0.203486,0.005887805,0.6676453,0.00479889,0.113109],"study_design_scores_gemma":[0.00001877196,0.0001519605,0.002241851,0.0004546533,0.0001296644,0.0003841547,0.002793365,0.3780468,0.004246276,0.5434102,0.06805752,0.0000647276],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03682599,0.003076495,0.9155663,0.005825795,0.0002214241,0.0001895218,0.0001611013,0.0005847523,0.03754856],"genre_scores_gemma":[0.6763148,0.003892884,0.3071087,0.0004719927,0.0001606352,0.000283932,0.0002048637,0.0001452584,0.01141693],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003103644,"threshold_uncertainty_score":0.01031715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006927732514470165,"score_gpt":0.237400704250108,"score_spread":0.2304729717356378,"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."}}