{"id":"W2888982173","doi":"10.3390/en11092286","title":"Hydrothermal Carbonization of Biosolids from Waste Water Treatment Plant","year":2018,"lang":"en","type":"article","venue":"Energies","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health PEI; University of Prince Edward Island; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hydrothermal carbonization; Biosolids; Carbonization; Heat of combustion; Nitrogen; Carbon fibers; Sewage sludge; Phosphorus; Moisture; Hydrothermal circulation; Wastewater; Pulp and paper industry; Sewage treatment; Dewatering; Chemistry; Environmental chemistry; Waste management; Environmental science; Materials science; Chemical engineering; Environmental engineering; Combustion; Adsorption; Organic chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007118647,0.0002883309,0.0001476739,0.0002365728,0.000168525,0.0001732299,0.0001504258,0.0001770749,0.0009264745],"category_scores_gemma":[0.0001393267,0.00009104248,0.0002228636,0.0002634583,0.0001315303,0.0001893471,0.0001251981,0.0003120551,0.0001554982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002112008,"about_ca_system_score_gemma":0.0002391461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00162902,"about_ca_topic_score_gemma":0.004529208,"domain_scores_codex":[0.9999164,0.000009004002,0.000005894964,0.00001582283,0.00003287307,0.00001996661],"domain_scores_gemma":[0.9999505,0.00001055652,0.00001239788,0.000004181606,0.00001273817,0.000009522534],"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":[0.00004688686,0.00001075679,0.0001141982,0.00004527478,0.000003906916,0.0000519864,0.00001469586,0.0001599937,0.9980245,0.00003382181,0.00001644859,0.001477483],"study_design_scores_gemma":[0.00000404902,0.00007261183,0.001903806,0.000004666656,0.000004565671,0.00003624785,0.00001761947,0.0004539684,0.9969496,0.00002116786,0.0005282885,0.000003433273],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966372,0.0003719722,0.001431184,0.00002173796,0.00001443122,0.00002460384,0.0002122352,0.00002206766,0.001264453],"genre_scores_gemma":[0.9961033,0.0003762292,0.001740395,0.00001374486,0.000005704784,0.00001831383,0.0003263892,0.00001531974,0.001400766],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00162902,"threshold_uncertainty_score":0.003239036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006113335980898135,"score_gpt":0.1771050941725593,"score_spread":0.1709917581916611,"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."}}