{"id":"W2805951817","doi":"10.1002/wene.298","title":"Salvage harvesting for bioenergy in Canada: From sustainable and integrated supply chain to climate change mitigation","year":2018,"lang":"en","type":"article","venue":"Wiley Interdisciplinary Reviews Energy and Environment","topic":"Forest Biomass Utilization and Management","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Natural Resources Canada; University of British Columbia; Queen's University; Canadian Forest Service","funders":"Natural Resources Canada; BioFuelNet Canada","keywords":"Bioenergy; Biomass (ecology); Supply chain; Greenhouse gas; Environmental science; Natural resource economics; Raw material; Renewable energy; Climate change mitigation; Sustainability; Business; Biofuel; Waste management; Engineering; Economics; 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":[0.0001650663,0.000196841,0.0002482138,0.00009453783,0.0001062005,0.0000281485,0.0000798824,0.00004167828,0.00005561843],"category_scores_gemma":[0.000007784614,0.0001789396,0.00002385526,0.000106481,0.0000436838,0.0001325626,0.0002786229,0.0000358882,0.000003353089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003310285,"about_ca_system_score_gemma":0.000009432228,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04413386,"about_ca_topic_score_gemma":0.4562198,"domain_scores_codex":[0.9989735,0.0000356105,0.0003261029,0.0002797932,0.0000688786,0.0003161266],"domain_scores_gemma":[0.9996538,0.00002027068,0.00004354014,0.0001575113,0.000007153708,0.0001176868],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001773781,0.0001086102,0.01308314,0.001325593,0.0001116409,0.00006623084,0.004555335,0.003999901,0.002946401,0.0153109,0.02227006,0.9360448],"study_design_scores_gemma":[0.0006819512,0.0002833815,0.02100054,0.001142509,0.0000414957,0.000003805848,0.001942251,0.06342928,0.001272808,0.000743631,0.9088491,0.0006093142],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8963262,0.03879361,0.05156462,0.004090554,0.001133208,0.003520277,0.0003450715,0.0002306822,0.003995762],"genre_scores_gemma":[0.9806346,0.0158543,0.001500574,0.0005132932,0.0001367259,0.000724188,0.0002564573,0.00003644982,0.0003434364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9354355,"threshold_uncertainty_score":0.9622313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01285875533459814,"score_gpt":0.2167223127211255,"score_spread":0.2038635573865274,"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."}}