{"id":"W1791310834","doi":"10.1016/j.apenergy.2015.04.048","title":"Sustainable biomass supply chains from salvage logging of fire-killed stands: A case study for wood pellet production in eastern Canada","year":2015,"lang":"en","type":"article","venue":"Applied Energy","topic":"Forest Biomass Utilization and Management","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Canadian Forest Service; Natural Resources Canada","funders":"BioFuelNet Canada","keywords":"Biomass (ecology); Environmental science; Logging; Bioenergy; Raw material; Production (economics); Pellet; Sustainable forest management; Supply chain; Agroforestry; Forestry; Agricultural engineering; Forest management; Pulp and paper industry; Biofuel; Waste management; Agronomy; Business; Engineering; Ecology; Geography; Economics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004991781,0.0003941977,0.0002454371,0.001036782,0.006911005,0.002826291,0.00119684,0.0009629109,0.003664295],"category_scores_gemma":[0.001275908,0.0003185166,0.0004181995,0.002251775,0.001439096,0.0009234894,0.001308343,0.0009434673,0.0002124972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03208582,"about_ca_system_score_gemma":0.03107978,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9597271,"about_ca_topic_score_gemma":0.989867,"domain_scores_codex":[0.9994393,0.00006263188,0.00001467913,0.0000425849,0.0001150637,0.0003257271],"domain_scores_gemma":[0.9991898,0.000199501,0.00007725161,0.0000391007,0.0002566646,0.0002375657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001032231,0.001934559,0.5322191,0.000563241,0.0003285145,0.04208837,0.04195839,0.1454512,0.013267,0.03894929,0.009438999,0.1727692],"study_design_scores_gemma":[0.0002225377,0.0007411688,0.4471965,0.0005959157,0.0003225706,0.002799677,0.333702,0.1257339,0.007144785,0.01011791,0.07119113,0.0002318292],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906129,0.0001355122,0.0005955509,0.0002235115,0.000003858675,0.0000948899,0.0001841541,0.000013234,0.008136312],"genre_scores_gemma":[0.9929309,0.0002231394,0.001211711,0.00003533101,0.00000187968,0.00002078979,0.0001817397,0.00000810066,0.005386342],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04027289,"threshold_uncertainty_score":0.2328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01196097031832338,"score_gpt":0.2049636922811142,"score_spread":0.1930027219627908,"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."}}