{"id":"W3134231918","doi":"10.1016/j.energy.2021.120200","title":"Hydrothermal carbonization of miscanthus: Processing, properties, and synergistic Co-combustion with lignite","year":2021,"lang":"en","type":"article","venue":"Energy","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hydrothermal carbonization; Miscanthus; Combustion; Heat of combustion; Thermogravimetric analysis; Biomass (ecology); Carbonization; Solid fuel; Carbon fibers; Chemical engineering; Chemistry; Biofuel; Pulp and paper industry; Materials science; Waste management; Bioenergy; Organic chemistry; Composite number; Agronomy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00001728772,0.00009025354,0.0001061653,0.00003367945,0.00002258139,0.00001603928,0.0000426468,0.00004975328,0.00003498887],"category_scores_gemma":[0.00001471427,0.00007572069,0.000009296438,0.0001689809,0.00005303646,0.00007023253,0.00001097621,0.00003359606,7.429773e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001862213,"about_ca_system_score_gemma":0.00004024012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001889035,"about_ca_topic_score_gemma":0.00001040306,"domain_scores_codex":[0.9995642,0.00001040656,0.0001083081,0.0001174187,0.0001020395,0.00009766685],"domain_scores_gemma":[0.9997699,0.000009421865,0.00002855755,0.00008268987,0.00007069484,0.00003875883],"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":[0.00001792813,0.00001745306,0.0001736667,0.0003303402,0.00002289081,0.000009007552,0.0001447426,0.001490921,0.9914562,0.0001692876,0.00004737388,0.006120219],"study_design_scores_gemma":[0.0001991625,0.00001714989,0.00004800133,0.0001427611,0.00001780142,0.00001046094,0.00004846814,0.00522575,0.9935802,0.00002186202,0.0005778598,0.000110549],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882285,0.004232953,0.004550588,0.00003119122,0.00003794445,0.00003269487,0.000004160405,0.0001557946,0.002726183],"genre_scores_gemma":[0.9993656,0.00007641318,0.0002109121,0.00001998824,0.00002280009,0.000007658532,0.00001909617,0.00002385577,0.0002536618],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01113712,"threshold_uncertainty_score":0.30878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007456760108192247,"score_gpt":0.172233453889543,"score_spread":0.1647766937813507,"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."}}