{"id":"W4238809751","doi":"10.5194/gmd-2019-261-supplement","title":"Supplementary material to \"Quantitative assessment of fire and vegetation properties in historical simulations with fire-enabled vegetation models from the Fire Model Intercomparison Project\"","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Impact; Environment and Climate Change Canada","funders":"","keywords":"Vegetation (pathology); Environmental science; Environmental resource management; Physical geography; Forestry; Geography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001322896,0.002067913,0.001168862,0.001621758,0.0005262563,0.001414245,0.002467611,0.001585776,0.6510293],"category_scores_gemma":[0.01035516,0.0008965369,0.0009078796,0.002477272,0.0002493243,0.001345562,0.001252516,0.001204426,0.1809022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008170799,"about_ca_system_score_gemma":0.00115836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006787765,"about_ca_topic_score_gemma":0.005585731,"domain_scores_codex":[0.999377,0.0001164627,0.00008549655,0.0001337554,0.0002008674,0.00008646617],"domain_scores_gemma":[0.9940839,0.003390833,0.0002611407,0.0007452344,0.001228127,0.0002906162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001331509,0.000265377,0.0006192938,0.0007196781,0.00009629062,0.0001162945,0.00004421786,0.004844631,0.001043254,0.006205999,0.9706215,0.01529035],"study_design_scores_gemma":[0.002187678,0.0002119831,0.0105061,0.0003576695,0.0001153885,0.0005647565,0.0001356332,0.06054806,0.008089475,0.05405387,0.863026,0.0002035751],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002928753,0.0001619627,0.02553177,0.0009092437,0.002293217,0.0001302833,0.9471589,0.007689469,0.01319635],"genre_scores_gemma":[0.02165413,0.0003567904,0.02784655,0.0005395145,0.0009981996,0.000545712,0.9146043,0.008978838,0.02447605],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6510293,"threshold_uncertainty_score":0.4977643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0494703342533617,"score_gpt":0.284840576634697,"score_spread":0.2353702423813353,"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."}}