{"id":"W4362684801","doi":"10.1071/wf22112","title":"Evaluation of new methods for drought estimation in the Canadian Forest Fire Danger Rating System","year":2023,"lang":"en","type":"article","venue":"International Journal of Wildland Fire","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University; Western University; Environment and Climate Change Canada; Canadian Forest Service; University of Toronto; Natural Resources Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Space Agency; Natural Resources Canada; Environment and Climate Change Canada; National Aeronautics and Space Administration","keywords":"Water content; Environmental science; Soil water; Moisture; Soil science; Fire regime; Taiga; Hydrology (agriculture); Meteorology; Ecosystem; Geology; Forestry; Geography; Ecology; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.009285197,0.001231961,0.000635723,0.002239571,0.00119841,0.001506392,0.001961093,0.0006211649,0.00215359],"category_scores_gemma":[0.02632971,0.0004247651,0.000555852,0.001565898,0.0003580721,0.001128895,0.001196333,0.0009805065,0.0004567927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007455434,"about_ca_system_score_gemma":0.007351538,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.748508,"about_ca_topic_score_gemma":0.7033703,"domain_scores_codex":[0.9961015,0.001161774,0.0002646424,0.0006750814,0.00151367,0.0002832702],"domain_scores_gemma":[0.9834166,0.005908567,0.0007155431,0.0006243774,0.008893328,0.0004415082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001625138,0.000448235,0.1992722,0.0004249057,0.0005280014,0.0001248652,0.0004750635,0.2128536,0.006542205,0.002202414,0.006894736,0.5686086],"study_design_scores_gemma":[0.0001203728,0.0001388164,0.05124191,0.00004639171,0.00007481656,0.00004805204,0.0001714492,0.9440941,0.001945648,0.0003734348,0.001688869,0.00005629603],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5352378,0.001617414,0.437185,0.001015458,0.000356953,0.002151099,0.005956117,0.00586516,0.01061505],"genre_scores_gemma":[0.7030137,0.0005071806,0.2899568,0.0001442058,0.00007152635,0.0004850507,0.003412363,0.0001774104,0.002231744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.251492,"threshold_uncertainty_score":0.5059462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03394703434309729,"score_gpt":0.3473418136187004,"score_spread":0.3133947792756031,"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."}}