{"id":"W2477903795","doi":"10.1111/gcbb.12387","title":"Climate change mitigation potential of local use of harvest residues for bioenergy in Canada","year":2016,"lang":"en","type":"article","venue":"GCB Bioenergy","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"Canadian Forest Service; Government of Canada","keywords":"Bioenergy; Environmental science; Climate change; Climate change mitigation; Electricity; Greenhouse gas; Agroforestry; Environmental protection; Biofuel; Ecology; Engineering; 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":[],"consensus_categories":[],"category_scores_codex":[0.00007820952,0.00009521619,0.0001358481,0.00006702654,0.00002356969,0.000005651928,0.0001434512,0.00003797122,0.0003068347],"category_scores_gemma":[0.00001248147,0.0000715874,0.00003944949,0.0001593711,0.000168406,0.0002449374,0.000109357,0.00001464979,0.000009776355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001571649,"about_ca_system_score_gemma":0.00002639908,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.904205,"about_ca_topic_score_gemma":0.9594435,"domain_scores_codex":[0.9991174,0.00002469755,0.0002480016,0.0001724333,0.0001739485,0.0002634628],"domain_scores_gemma":[0.9996108,0.00003183683,0.0001241619,0.000174152,0.000009039283,0.00004996324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005716623,0.0002427296,0.5514693,0.0002133361,0.00005862516,0.00002562299,0.0002247869,0.00824534,0.0847653,0.04554056,0.04239337,0.2662493],"study_design_scores_gemma":[0.001668345,0.0003117244,0.7942098,0.0001881425,0.00003260748,0.000001719964,0.00006828227,0.003911012,0.1152859,0.0006431828,0.0832333,0.0004460629],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980046,0.00001890579,0.0003429885,0.0006969105,0.0001330969,0.0001277368,0.0001140401,0.000007389531,0.0005543386],"genre_scores_gemma":[0.9985172,0.0001245351,0.0003062217,0.0001570721,0.00004593647,0.00002738507,0.00002314344,0.00001054677,0.0007879239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2658033,"threshold_uncertainty_score":0.3359624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01750190760569962,"score_gpt":0.2091647839042906,"score_spread":0.191662876298591,"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."}}