{"id":"W2111457051","doi":"10.1111/gcbb.12055","title":"Damaged forests provide an opportunity to mitigate climate change","year":2013,"lang":"en","type":"article","venue":"GCB Bioenergy","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of British Columbia","funders":"Natural Resources Canada; FPInnovations; Universiteit Utrecht","keywords":"Environmental science; Slash (logging); Biomass (ecology); Bioenergy; Agroforestry; Logging; Carbon sequestration; Greenhouse gas; Climate change; Forestry; Agronomy; Ecology; Biofuel; Carbon dioxide; Geography; Biology","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":["insufficient_payload"],"category_scores_codex":[0.0001476626,0.0001640937,0.000114483,0.00006818477,0.0001477968,0.00008689542,0.0003718387,0.00005147372,0.0109263],"category_scores_gemma":[0.00002944766,0.0001433451,0.0000402156,0.0002450575,0.0001009,0.0006687552,0.000421841,0.00006092829,0.007910497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004081379,"about_ca_system_score_gemma":0.000005568057,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01214178,"about_ca_topic_score_gemma":0.007639971,"domain_scores_codex":[0.9987383,0.0000555711,0.0001593394,0.0003126417,0.0002005179,0.0005336626],"domain_scores_gemma":[0.9988729,0.000008476341,0.00005295446,0.0004354881,0.000006762555,0.0006234528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00005033434,0.0003720134,0.3252752,0.00004822691,0.00002877644,0.00005551658,0.001923265,0.0006568291,0.00804168,0.01172466,0.2360068,0.4158167],"study_design_scores_gemma":[0.0003370281,0.0003643535,0.6161713,0.00001955243,0.00001471697,0.000003064308,0.00004442609,0.003655113,0.0008492389,0.00118654,0.3768311,0.0005235886],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9401882,0.000004925553,0.000008402199,0.002988697,0.000121227,0.0004486244,0.00001059244,0.0001172434,0.05611209],"genre_scores_gemma":[0.9863216,0.00002027031,0.0004762067,0.005622445,0.0001721832,0.0002486992,0.00004854993,0.0000244242,0.007065635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4152931,"threshold_uncertainty_score":0.9944364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03459833559872455,"score_gpt":0.2575276076247545,"score_spread":0.22292927202603,"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."}}