{"id":"W4311946825","doi":"10.3389/ffgc.2022.1040408","title":"Evaluation of geographically weighted logistic model and mixed effect model in forest fire prediction in northeast China","year":2022,"lang":"en","type":"article","venue":"Frontiers in Forests and Global Change","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Logistic regression; Environmental science; Vegetation (pathology); China; Fire prevention; Physical geography; Geography; Predictive modelling; Forest management; Forestry; Statistics; Mathematics; Engineering","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":[0.005129267,0.001320471,0.0009600346,0.00170651,0.0004928056,0.001126962,0.00160973,0.0006494122,0.001617199],"category_scores_gemma":[0.006521356,0.0004320776,0.002049959,0.001009899,0.0003117266,0.001186949,0.0009935404,0.0008758586,0.0002986692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001019678,"about_ca_system_score_gemma":0.001499109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05054562,"about_ca_topic_score_gemma":0.02864792,"domain_scores_codex":[0.9983872,0.0008682483,0.0001003949,0.0003497226,0.000145306,0.000149035],"domain_scores_gemma":[0.9967644,0.002100122,0.000254657,0.0001516678,0.0005309213,0.0001982406],"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":[0.0007164946,0.0003322393,0.3373845,0.0002014803,0.0006136433,0.0005104856,0.000247695,0.5677835,0.0006909234,0.001540448,0.001721361,0.08825722],"study_design_scores_gemma":[0.00001774887,0.00006806655,0.01242689,0.00001314619,0.00006603059,0.00002608294,0.00005411374,0.9866211,0.0001111636,0.0003843991,0.000199805,0.00001143149],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9193571,0.001435127,0.07572736,0.0008010744,0.0000817721,0.00008636459,0.0006738704,0.0003882697,0.001449054],"genre_scores_gemma":[0.9872427,0.0003686399,0.01063012,0.00003892961,0.00004023257,0.00005902137,0.0007004712,0.00002483569,0.0008950055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05054562,"threshold_uncertainty_score":0.1005028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01593748370796895,"score_gpt":0.2322015378442536,"score_spread":0.2162640541362846,"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."}}