{"id":"W2905204594","doi":"","title":"Ontario’s managed forests and harvested wood products contribute to greenhouse gas mitigation from 2020 to 2100","year":2018,"lang":"en","type":"article","venue":"The Forestry Chronicle","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Greenhouse gas; Baseline (sea); Forestry; Environmental science; Business as usual; Carbon stock; Forest management; Wood production; Agroforestry; Geography; Climate change; Ecology; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0003304125,0.000353488,0.0001716948,0.0005286195,0.0007216897,0.001172505,0.0004236704,0.0003207793,0.003148879],"category_scores_gemma":[0.0006285941,0.0002328726,0.0005851064,0.000992981,0.0002896191,0.0005825881,0.0003976416,0.000221402,0.00021743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02374911,"about_ca_system_score_gemma":0.02009804,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9679151,"about_ca_topic_score_gemma":0.9841765,"domain_scores_codex":[0.9997305,0.00002287518,0.000006732909,0.00002924922,0.000109015,0.0001016367],"domain_scores_gemma":[0.9997239,0.00002339817,0.00004173705,0.000008791542,0.0001494063,0.0000527407],"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":[0.0004475079,0.0000899527,0.5477732,0.0007804706,0.0006985206,0.0007349001,0.001084646,0.2851471,0.004271667,0.02462734,0.05076837,0.08357629],"study_design_scores_gemma":[0.0001245059,0.00009096809,0.620235,0.0003447921,0.0005102741,0.0001716125,0.002268157,0.1653206,0.002082848,0.007543807,0.201208,0.00009934718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8157252,0.004000388,0.005314087,0.005017695,0.0001122419,0.0001740552,0.04759717,0.0002323979,0.1218269],"genre_scores_gemma":[0.9821081,0.001410381,0.001993506,0.0001797291,0.00001308073,0.00003537892,0.006335335,0.00002351127,0.007901041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03208494,"threshold_uncertainty_score":0.1723127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009167904794671564,"score_gpt":0.2208811566998848,"score_spread":0.2117132519052132,"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."}}