{"id":"W2118996602","doi":"10.1007/s10584-009-9572-8","title":"Biological Carbon Sequestration and Carbon Trading Re-Visited","year":2009,"lang":"en","type":"article","venue":"Data Archiving and Networked Services (DANS)","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Carbon offset; Greenhouse gas; Natural resource economics; Carbon sink; Carbon credit; Climate change; Environmental science; Emissions trading; Carbon sequestration; Deforestation (computer science); Climate change mitigation; Carbon fibers; Offset (computer science); Business; Environmental protection; Carbon dioxide; Economics; Ecology; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.001448046,0.0003304853,0.0002718504,0.0008397499,0.0009697417,0.005094047,0.0007113897,0.001779474,0.01229423],"category_scores_gemma":[0.005036206,0.0001613361,0.0002643639,0.001138266,0.002942708,0.005678534,0.001625272,0.001183896,0.0008455406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003634267,"about_ca_system_score_gemma":0.002049742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005326995,"about_ca_topic_score_gemma":0.008380845,"domain_scores_codex":[0.9990711,0.0003442352,0.00005208889,0.0001292242,0.0002737312,0.0001296301],"domain_scores_gemma":[0.9977284,0.00107457,0.000292804,0.0003731491,0.0003403493,0.0001906863],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008440529,0.00003561628,0.002895348,0.00006297979,0.00001165787,0.0001861433,0.0001983461,0.006512273,0.0007932438,0.9362724,0.003028253,0.04991925],"study_design_scores_gemma":[0.00001045112,0.00003882329,0.003498951,0.0001695072,0.00001738789,0.0003634415,0.0007390275,0.02590545,0.002067257,0.9064903,0.06066966,0.00002981338],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2045256,0.02451617,0.06080869,0.04399246,0.001473513,0.00006866302,0.0003892975,0.0001522291,0.6640733],"genre_scores_gemma":[0.9645622,0.003648428,0.004046853,0.0004541759,0.0001888836,0.00002192736,0.00007249482,0.00002106394,0.02698388],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01229423,"threshold_uncertainty_score":0.04112828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02330211919372025,"score_gpt":0.2478207849573939,"score_spread":0.2245186657636737,"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."}}