{"id":"W2143915124","doi":"10.5194/bg-11-3515-2014","title":"Quantifying the biophysical climate change mitigation potential of Canada's forest sector","year":2014,"lang":"en","type":"article","venue":"Biogeosciences","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":192,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"U.S. Forest Service; Canadian Forest Service; Government of Canada; Australian Government; Strong","keywords":"Greenhouse gas; Bioenergy; Environmental science; Carbon sequestration; Forest management; Climate change mitigation; Climate change; Forest product; Agroforestry; Natural resource economics; Renewable energy; Ecology; Carbon dioxide; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026928,0.00006881741,0.00006604892,0.00002057237,0.0002434285,0.00002983868,0.0003183747,0.00001644607,0.000272695],"category_scores_gemma":[0.00002390783,0.000042618,0.00003100436,0.0002954603,0.0003643616,0.0001463019,0.0001326565,0.00002892214,0.00006087322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002262988,"about_ca_system_score_gemma":0.00001189898,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4159809,"about_ca_topic_score_gemma":0.4237831,"domain_scores_codex":[0.9991061,0.00003528617,0.0001077016,0.0001550725,0.0003466709,0.0002491341],"domain_scores_gemma":[0.9997051,0.00002822518,0.00007965434,0.0001380022,0.000004122925,0.00004485542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001527097,0.00008469339,0.9322529,0.00003725529,0.000006970473,0.000002057279,0.0005915574,0.0003925989,0.01675233,0.02866178,0.01007889,0.01112368],"study_design_scores_gemma":[0.00008018567,0.00007786659,0.9469874,0.000009993125,0.000008974643,7.863077e-7,0.00005414751,0.03452802,0.001009482,0.0002933574,0.01683509,0.0001146898],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992733,0.000006261671,0.00002640072,0.001332335,0.0002934715,0.000118315,0.00001086475,0.00001108678,0.005468234],"genre_scores_gemma":[0.9993581,0.000008005517,0.00007969801,0.0002730234,0.000132155,0.00000853062,0.000003152509,0.000003002655,0.00013431],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03413542,"threshold_uncertainty_score":0.5879081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02167617978753549,"score_gpt":0.2323591882949066,"score_spread":0.2106830085073712,"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."}}