{"id":"W4246967671","doi":"10.5194/nhessd-3-6997-2015","title":"Calibration and evaluation of the Canadian Forest Fire Weather Index (FWI) System for improved wildland fire danger rating in the UK","year":2015,"lang":"en","type":"preprint","venue":"","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Environment Research Council","keywords":"Environmental science; Meteorology; Calibration; Percentile; Geography; Statistics; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003195984,0.000522825,0.0003071115,0.001022087,0.0006257786,0.001068372,0.000952946,0.0004316574,0.001284385],"category_scores_gemma":[0.01283745,0.0002835793,0.0002774177,0.001463212,0.0002776468,0.0005240686,0.0006249915,0.0005606824,0.0006444526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004963837,"about_ca_system_score_gemma":0.002865301,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6884657,"about_ca_topic_score_gemma":0.7164848,"domain_scores_codex":[0.9985979,0.0002769518,0.0000823344,0.0002674551,0.0006352309,0.0001400388],"domain_scores_gemma":[0.9955102,0.0006783566,0.000330089,0.0003066808,0.002957599,0.0002171749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000724233,0.0003214535,0.5237811,0.000177874,0.0001727392,0.0002386704,0.001061208,0.2310357,0.01243785,0.0009492476,0.01324166,0.2158583],"study_design_scores_gemma":[0.00006376424,0.0001453358,0.5662221,0.00006841101,0.00004888294,0.00008002971,0.000444913,0.4205984,0.005870998,0.0001540978,0.006183763,0.0001194032],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9470595,0.0001641054,0.03682606,0.0001870532,0.00006667984,0.000412341,0.005307374,0.001503362,0.008473418],"genre_scores_gemma":[0.963407,0.000066432,0.03053737,0.00004176609,0.000007007653,0.0001105479,0.004586189,0.0001226368,0.0011211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6884657,"threshold_uncertainty_score":0.6267381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01942328498724788,"score_gpt":0.2416789323892757,"score_spread":0.2222556474020278,"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."}}