{"id":"W4239238158","doi":"10.5194/bgd-11-441-2014","title":"Quantifying the biophysical climate change mitigation potential of Canada's forest sector","year":2014,"lang":"en","type":"preprint","venue":"","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":12,"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; Environmental science; Bioenergy; Carbon sequestration; Forest management; Climate change mitigation; Climate change; Forest product; Agroforestry; Natural resource economics; Renewable energy; Ecology; Economics; Carbon dioxide","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001780923,0.0001625828,0.0001648279,0.00002280675,0.0001117772,0.00003411511,0.000403424,0.00007615762,0.001556307],"category_scores_gemma":[0.00001041442,0.0001100916,0.00008687592,0.000079391,0.0001380863,0.00005061682,0.001025515,0.00016601,0.0001386876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008992002,"about_ca_system_score_gemma":0.00002072683,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6168103,"about_ca_topic_score_gemma":0.6696736,"domain_scores_codex":[0.9988483,0.0000495957,0.0002005036,0.0002498648,0.0003678456,0.0002839089],"domain_scores_gemma":[0.9993682,0.00002528623,0.0001726893,0.0003745219,0.000005895143,0.0000534245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000177948,0.000525655,0.4101357,0.002398185,0.0003504049,0.00003761645,0.002444837,0.1156129,0.006913976,0.09526896,0.347748,0.01838584],"study_design_scores_gemma":[0.000301641,0.00007610162,0.7155753,0.0001226759,0.0001235365,0.000001532085,0.00004316652,0.2647218,0.0007333257,0.001655806,0.01602239,0.0006226994],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9691981,0.000007121448,0.0001137985,0.001995252,0.0005700654,0.0004796213,0.00003341249,0.00002768334,0.02757496],"genre_scores_gemma":[0.9983187,0.00001961425,0.0001178371,0.000393077,0.0003408854,0.0000387851,0.00004699788,0.00001454215,0.0007095233],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3317257,"threshold_uncertainty_score":0.9993564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02581236273476903,"score_gpt":0.2432536372206897,"score_spread":0.2174412744859207,"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."}}