{"id":"W4288926139","doi":"10.1016/j.envsoft.2022.105473","title":"The Dynamic Temperate and Boreal Fire and Forest-Ecosystem Simulator (DYNAFFOREST): Development and evaluation","year":2022,"lang":"en","type":"article","venue":"Environmental Modelling & Software","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agricultural Research Institute, California State University; National Institute of Food and Agriculture; Environmental Defense Fund; U.S. Department of Energy; Gordon and Betty Moore Foundation; Royal Bank of Canada; University of California; Zegar Family Foundation; National Science Foundation","keywords":"Biome; Taiga; Boreal; Temperate climate; Environmental science; Disturbance (geology); Temperate rainforest; Temperate forest; Fire regime; Climate change; Forest dynamics; Forest ecology; Boreal ecosystem; Fire ecology; Ecosystem; Environmental resource management; Ecology; Geography; Physical geography; Forestry; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001601917,0.001055692,0.0005041468,0.0003867871,0.0004404576,0.0005199775,0.002185932,0.0006830606,0.00287502],"category_scores_gemma":[0.002808003,0.0004257244,0.0006846847,0.0005270736,0.0005616324,0.0008282741,0.0008248801,0.001152386,0.000363364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0010439,"about_ca_system_score_gemma":0.001704729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04692101,"about_ca_topic_score_gemma":0.05843686,"domain_scores_codex":[0.9996368,0.0001237956,0.00002695966,0.00005496793,0.00009669582,0.00006087489],"domain_scores_gemma":[0.9987921,0.0006425311,0.00006111912,0.00009767125,0.0002073484,0.0001993491],"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":[0.0002963112,0.0003247881,0.01282717,0.0001685126,0.0001285833,0.0001186193,0.00011982,0.9599272,0.001450114,0.003235738,0.008892665,0.01251048],"study_design_scores_gemma":[0.0001339923,0.00008148362,0.001843346,0.00001105248,0.00001688395,0.00002477908,0.0000327224,0.9928646,0.0008268025,0.0006272077,0.003521034,0.00001603013],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9013391,0.0007773567,0.04722703,0.0007950364,0.000430623,0.0004571426,0.01825976,0.00716611,0.02354788],"genre_scores_gemma":[0.9211714,0.0004475729,0.05972902,0.000236465,0.00004078693,0.0003653109,0.01440746,0.001068059,0.002533907],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04692101,"threshold_uncertainty_score":0.09329581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007383606729635929,"score_gpt":0.1994371643658096,"score_spread":0.1920535576361737,"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."}}