{"id":"W2913267024","doi":"10.1021/acs.energyfuels.8b03454","title":"Catalyzed Hydrothermal Carbonization with Process Liquid Recycling","year":2019,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hydrothermal carbonization; Chemical engineering; Carbonization; Carbon fibers; Coal; Chemistry; Pellets; Yield (engineering); Pyrolysis; Biofuel; Catalysis; Materials science; Waste management; Organic chemistry; Composite number; Adsorption; Composite material","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":[0.00003937612,0.0001539164,0.0001487651,0.00005921026,0.00002339523,0.00002064588,0.0001648535,0.00008984904,0.0002753803],"category_scores_gemma":[0.000009376047,0.0001354926,0.00002486655,0.0002681071,0.00002021278,0.0001798261,0.00001754988,0.00007324426,0.00006363809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003823758,"about_ca_system_score_gemma":0.00002542863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001486434,"about_ca_topic_score_gemma":0.00000578693,"domain_scores_codex":[0.9992744,0.000009387175,0.0001396019,0.0002005024,0.0001623261,0.000213801],"domain_scores_gemma":[0.9996185,0.00002836095,0.00003335346,0.0002029595,0.00004938569,0.00006738693],"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":[0.00006358544,0.00001075853,0.0002308446,0.0001093689,0.00003670828,0.000003952768,0.0001517365,0.002494067,0.9958161,0.0001871678,0.00001590145,0.000879816],"study_design_scores_gemma":[0.0003339999,0.00003689301,0.00001593987,0.00005318827,0.00001054419,0.0000051184,0.00003722208,0.0004633097,0.9979492,0.00006993993,0.0008135051,0.0002110891],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904109,0.0003294571,0.0007109455,0.00003006917,0.000139612,0.00006574719,0.000002185811,0.000433469,0.007877585],"genre_scores_gemma":[0.9992666,0.00002209411,0.0001212347,0.00005303482,0.00006345862,0.00002053002,0.00002810732,0.00005888676,0.0003660411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008855685,"threshold_uncertainty_score":0.5525228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00394265919868497,"score_gpt":0.1836722411489021,"score_spread":0.1797295819502172,"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."}}