{"id":"W3184235702","doi":"10.3390/en14154493","title":"Miscanthus to Biocarbon for Canadian Iron and Steel Industries: An Innovative Approach","year":2021,"lang":"en","type":"article","venue":"Energies","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Environment and Climate Change Canada; Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Agriculture, Food and Rural Affairs","keywords":"Pyrolysis; Miscanthus; Biomass (ecology); Hydrothermal carbonization; Coal; Carbonization; Waste management; Environmental science; Carbon fibers; Greenhouse gas; Pulp and paper industry; Biofuel; Renewable energy; Bioenergy; Materials science; Agronomy; Engineering","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":[0.0002575667,0.0007721621,0.0003617178,0.001368928,0.001084432,0.0009070328,0.0006332437,0.0004519637,0.002425528],"category_scores_gemma":[0.0001383617,0.0003186159,0.0008554372,0.00105771,0.0002940914,0.0004118002,0.0006079838,0.0004916225,0.0003051408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003185112,"about_ca_system_score_gemma":0.00711214,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.116831,"about_ca_topic_score_gemma":0.349732,"domain_scores_codex":[0.9996995,0.00001360519,0.000009545089,0.00005340472,0.0001654986,0.00005842126],"domain_scores_gemma":[0.9999218,0.000004635674,0.000011353,0.000004700259,0.00003966152,0.00001785538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002685452,0.0002807783,0.002946939,0.00143165,0.00006669419,0.0006640001,0.0002414814,0.007167071,0.803564,0.006018016,0.001226235,0.1761246],"study_design_scores_gemma":[0.0001287979,0.001675992,0.02253869,0.0002498582,0.0005820467,0.0007044674,0.0009369932,0.04256375,0.7207963,0.003086353,0.2065655,0.0001712515],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7865133,0.03075692,0.09001394,0.002568611,0.0003950929,0.001434356,0.001265758,0.0007352916,0.08631673],"genre_scores_gemma":[0.8927647,0.0148579,0.07034839,0.0002938161,0.00005523686,0.0002253162,0.0004993765,0.0000510332,0.0209042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.883169,"threshold_uncertainty_score":0.232302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01338584028922576,"score_gpt":0.2098390217169875,"score_spread":0.1964531814277617,"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."}}