{"id":"W2059527009","doi":"10.5558/tfc2012-112","title":"Carbon credits for cookstoves: Trade-offs in climate and health benefits","year":2012,"lang":"en","type":"article","venue":"The Forestry Chronicle","topic":"Energy and Environment Impacts","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; North Carolina State University","keywords":"Context (archaeology); Clean Development Mechanism; Business; Carbon credit; Greenhouse gas; Environmental economics; Natural resource economics; Economics; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004847799,0.0001122274,0.0001114832,0.00001085762,0.000142925,0.00001065887,0.0001279957,0.0000517651,0.00006580767],"category_scores_gemma":[0.000008388709,0.00008243351,0.00002380238,0.00006712024,0.0001341979,0.0001758144,0.0001011655,0.00009524432,0.00001631999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002144308,"about_ca_system_score_gemma":0.000009038593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004325245,"about_ca_topic_score_gemma":0.0005181115,"domain_scores_codex":[0.9989516,0.00002848847,0.0001464053,0.0001469467,0.0001229198,0.0006036828],"domain_scores_gemma":[0.9995553,0.00004608489,0.00005572469,0.0001942639,3.265372e-7,0.00014828],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001284847,0.0004606918,0.872515,0.00009864544,0.00002198918,0.000001644606,0.004457383,0.07032736,0.001878954,0.005303131,0.004472381,0.0403343],"study_design_scores_gemma":[0.0005762904,0.000128359,0.9915171,0.00002023247,0.000005433824,0.000009097836,0.00008487642,0.001557817,0.0006861479,0.0002765302,0.005018774,0.0001193479],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948354,0.00153113,0.000007721788,0.001540319,0.0000878275,0.0002256783,0.00001063562,0.00001949171,0.001741768],"genre_scores_gemma":[0.9987717,0.0003532935,0.0001026208,0.0005721398,0.00008312251,0.00002769618,0.000006861701,0.00001552335,0.00006698682],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1190021,"threshold_uncertainty_score":0.3361541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02692709881613416,"score_gpt":0.2554376757415289,"score_spread":0.2285105769253948,"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."}}