{"id":"W4401698749","doi":"10.3390/j7030018","title":"Unveiling Wildfire Dynamics: A Bayesian County-Specific Analysis in California","year":2024,"lang":"en","type":"article","venue":"J — Multidisciplinary Scientific Journal","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Precipitation; Elevation (ballistics); Natural disaster; Geography; Climate change; Bayesian probability; Physical geography; Population; Environmental science; Climatology; Demography; Meteorology; Ecology; Statistics; Mathematics","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","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004036048,0.0003582044,0.0004532209,0.001061856,0.0009367792,0.00147731,0.0007479665,0.0001565862,0.00252032],"category_scores_gemma":[0.00004851012,0.0003035373,0.0004173269,0.005192342,0.0004415702,0.001006849,0.0003577907,0.0008801631,0.002916811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002036717,"about_ca_system_score_gemma":0.00009634261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002342713,"about_ca_topic_score_gemma":0.003695634,"domain_scores_codex":[0.9956686,0.0002808633,0.0008973535,0.001089378,0.001178699,0.0008850431],"domain_scores_gemma":[0.9985721,0.0002040492,0.000181674,0.0006183452,0.00001956271,0.0004043018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009363298,0.0005922964,0.8565671,0.000118642,0.0003971121,0.003497012,0.006945475,0.06224279,0.008996372,0.00007729685,0.01744229,0.04303],"study_design_scores_gemma":[0.0002827974,0.00004303216,0.08167862,0.0001714911,0.00008942538,0.0002629333,0.0007452322,0.9056668,0.00004347077,0.0003286385,0.0103027,0.0003848056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821699,0.001019203,0.009897275,0.0006551849,0.003810295,0.0003533112,0.0001403786,0.0001328795,0.00182161],"genre_scores_gemma":[0.99585,0.00002994005,0.001453315,0.0000117195,0.0001971984,0.00001590253,0.00007384508,0.00004456454,0.002323502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8434241,"threshold_uncertainty_score":0.9999416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006815662201573527,"score_gpt":0.2376439851022792,"score_spread":0.2308283229007057,"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."}}