{"id":"W2056213384","doi":"10.3390/d6010133","title":"Predicting Climate Change Impacts to the Canadian Boreal Forest","year":2014,"lang":"en","type":"article","venue":"Diversity","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service; University of British Columbia; Université de Montréal; University of Victoria","funders":"","keywords":"Vegetation (pathology); Biodiversity; Climate change; Productivity; Taiga; Environmental science; Boreal; Geography; Seasonality; Wetland; Physical geography; Species richness; Ecology; Climatology; Forestry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003919758,0.0004279689,0.0001563976,0.0008719433,0.0008927488,0.001101533,0.0005014323,0.0002591345,0.001108201],"category_scores_gemma":[0.001053855,0.0001567039,0.0004485434,0.00107786,0.00027782,0.0003197415,0.0003705849,0.0003220635,0.0001344063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01147755,"about_ca_system_score_gemma":0.01010071,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9847952,"about_ca_topic_score_gemma":0.991211,"domain_scores_codex":[0.9998307,0.00001702014,0.000006756812,0.00003946534,0.00004966817,0.00005622513],"domain_scores_gemma":[0.9996248,0.00005463238,0.00003970601,0.00001294729,0.0002072932,0.00006053145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000111974,0.00005947066,0.7790688,0.00008332018,0.0001476281,0.0001268179,0.0001944638,0.1908676,0.001148033,0.000978785,0.002722875,0.02449036],"study_design_scores_gemma":[0.0000344364,0.00004921458,0.7236471,0.00004087369,0.00008962577,0.00005307083,0.0006896292,0.2678454,0.0008133713,0.0005719844,0.006127459,0.00003785249],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879563,0.0003845601,0.001662077,0.0003096399,0.00001848742,0.00003691074,0.005082358,0.0001038358,0.004445795],"genre_scores_gemma":[0.9949659,0.0002629154,0.001820994,0.00003142533,0.00000512689,0.00001275538,0.002153711,0.000007898682,0.0007393019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01520485,"threshold_uncertainty_score":0.08327579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0125352739517042,"score_gpt":0.1923200059414334,"score_spread":0.1797847319897292,"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."}}