{"id":"W3017928061","doi":"10.1016/j.rser.2020.109745","title":"Process simulation, techno-economic evaluation and market analysis of supply chains for torrefied wood pellets from British Columbia: Impacts of plant configuration and distance to market","year":2020,"lang":"en","type":"article","venue":"Renewable and Sustainable Energy Reviews","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Science and Engineering Research Council; Natural Sciences and Engineering Research Council of Canada; China Scholarship Council; Korea Institute of Science and Technology","keywords":"Torrefaction; Pelletizing; Pellets; Raw material; Production (economics); Capital cost; Business; Electricity; Industrial organization; Waste management; Environmental science; Engineering; Economics; Pyrolysis","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":[0.0008868741,0.000677416,0.000618395,0.001175764,0.001148013,0.001756611,0.001006031,0.001238419,0.004980044],"category_scores_gemma":[0.001887096,0.0006336938,0.0009417102,0.001598597,0.000595568,0.001134083,0.0004884979,0.001114213,0.0003488679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00951301,"about_ca_system_score_gemma":0.00461765,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5590848,"about_ca_topic_score_gemma":0.4661345,"domain_scores_codex":[0.9996896,0.00007408238,0.00001533448,0.00004614296,0.00006552098,0.0001093362],"domain_scores_gemma":[0.9981112,0.001278754,0.000089847,0.00005826779,0.0003893396,0.00007263442],"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":[0.000386405,0.0003507316,0.009574804,0.00005635211,0.00003025242,0.0001191927,0.00006170639,0.9803627,0.001479511,0.001083814,0.0004083432,0.006086139],"study_design_scores_gemma":[0.00004281589,0.0001177654,0.004370323,0.000004367983,0.00002228607,0.000007986633,0.0001948128,0.9933259,0.001204322,0.0003340951,0.0003615113,0.00001379557],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992363,0.00007189842,0.001496768,0.0001312226,0.000008384771,0.00006791248,0.0005310431,0.00003465211,0.005295143],"genre_scores_gemma":[0.9955492,0.00009082204,0.001042139,0.00001270151,0.000002327624,0.00004550372,0.000425678,0.00001343872,0.002818086],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4409152,"threshold_uncertainty_score":0.8870236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0085311334841614,"score_gpt":0.227269086453743,"score_spread":0.2187379529695816,"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."}}