{"id":"W3199184857","doi":"10.4236/jsbs.2021.113010","title":"A Cost Analysis of Mobile and Stationary Pellet Mills for Mitigating Wildfire Costs","year":2021,"lang":"en","type":"article","venue":"Journal of Sustainable Bioenergy Systems","topic":"Forest Biomass Utilization and Management","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Pellet; Pellets; Pelletizing; Environmental science; Biomass (ecology); Raw material; Bioenergy; Pulp and paper industry; Waste management; Agricultural engineering; Biofuel; Engineering; Agronomy; Chemistry; Materials science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.0003714091,0.0001004558,0.0003497342,0.0004127396,0.00005180224,0.00005564615,0.00007056812,0.0000505197,0.000007901341],"category_scores_gemma":[0.00009281193,0.00009495169,0.0001197148,0.0007042568,0.00002764079,0.0001507296,0.00002512605,0.00003899503,1.342209e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002130985,"about_ca_system_score_gemma":0.00007150496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005565958,"about_ca_topic_score_gemma":0.00002487491,"domain_scores_codex":[0.9989085,0.00003755985,0.0005430489,0.00009066359,0.0002383839,0.0001819019],"domain_scores_gemma":[0.9988206,0.00006675829,0.0002396755,0.0001058866,0.0006843046,0.00008279213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008813092,0.0001435035,0.004816688,0.003378315,0.005015665,0.0003700004,0.001113859,0.9351338,0.004522645,0.02862709,0.01088038,0.005909925],"study_design_scores_gemma":[0.002145102,0.0005133288,0.004210733,0.0007649212,0.001709424,0.0001079368,0.1305647,0.4424752,0.00485633,0.0001102486,0.4120202,0.0005218385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8768152,0.03673621,0.08249206,0.0001598313,0.0008369467,0.0009126876,0.00007874388,0.00006486353,0.001903476],"genre_scores_gemma":[0.9979694,0.0004858139,0.0005156125,0.00001723137,0.00005298022,0.00002987336,0.00002218319,0.00001673169,0.0008901652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4926586,"threshold_uncertainty_score":0.3872018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009634944451552522,"score_gpt":0.2374950665903171,"score_spread":0.2278601221387646,"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."}}