{"id":"W2159568318","doi":"10.1385/abab:105:1-3:231","title":"Wood-Ethanol for Climate Change Mitigation in Canada","year":2003,"lang":"en","type":"article","venue":"Applied Biochemistry and Biotechnology","topic":"Bioenergy crop production and management","field":"Agricultural and Biological Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"Canadian Forest Service; Government of Canada","keywords":"Greenhouse gas; Climate change mitigation; Environmental science; United Nations Framework Convention on Climate Change; Biomass (ecology); Carbon offset; Fossil fuel; Ethanol fuel; Carbon sequestration; Climate change; Waste management; Environmental protection; Natural resource economics; Biofuel; Carbon dioxide; Kyoto Protocol; Engineering; Ecology","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":[0.00008007415,0.00008838686,0.00009065386,0.000008208382,0.00007243019,0.000008537409,0.0000746916,0.0001575712,0.00002504086],"category_scores_gemma":[0.00001144126,0.0000429766,0.00001308657,0.0001616967,0.0000490544,0.0000134868,0.00003246083,0.00007045348,9.272824e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004473523,"about_ca_system_score_gemma":0.00001264783,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01810884,"about_ca_topic_score_gemma":0.1128389,"domain_scores_codex":[0.9993542,0.000005290701,0.0001081482,0.0002723277,0.00004232202,0.0002176729],"domain_scores_gemma":[0.9998583,0.00001432931,0.00004121508,0.00004685451,0.000009357425,0.0000300122],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001198725,0.00002013021,0.000207364,0.00002491132,0.000003819919,8.582463e-7,0.000004670439,1.568528e-7,0.8996088,0.01122315,0.0001778304,0.08871633],"study_design_scores_gemma":[0.00015322,0.00002283203,0.0007145959,0.000004740432,0.00000345532,0.0000042913,0.0004597681,0.000005126136,0.9415974,0.0006403044,0.05627558,0.0001186628],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914635,0.0001673886,0.000003403502,0.007228381,0.00006398893,0.0002289537,0.00001898562,0.00003917915,0.000786236],"genre_scores_gemma":[0.9989088,0.0002524505,0.0001601281,0.0004264903,0.00004816174,0.0001251876,0.00003993464,6.225734e-7,0.00003819606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09473005,"threshold_uncertainty_score":0.9884297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01076361370614009,"score_gpt":0.1825321582383803,"score_spread":0.1717685445322402,"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."}}