{"id":"W2592467855","doi":"10.1021/acs.energyfuels.7b00093","title":"Optimization and Characterization of Hydrochar Derived from Shrimp Waste","year":2017,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Schlumberger Foundation","keywords":"Hydrothermal carbonization; Shrimp; Lignocellulosic biomass; Biomass (ecology); Environmentally friendly; Pulp and paper industry; Environmental science; Sewage sludge; Heat of combustion; Carbonization; Biofuel; Waste management; Chemistry; Sewage treatment; Environmental engineering; Combustion; Fishery; Agronomy; Ecology; Biology","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":[0.0003139305,0.0003390721,0.0002443502,0.0003704618,0.0001475316,0.0003676866,0.0001574908,0.0002373223,0.0005649927],"category_scores_gemma":[0.0002853003,0.0001437088,0.0003488571,0.0004589973,0.0001714124,0.0002153917,0.0001749786,0.000400437,0.0002030406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001590122,"about_ca_system_score_gemma":0.0002321946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004072975,"about_ca_topic_score_gemma":0.001165512,"domain_scores_codex":[0.9998366,0.00001946885,0.00001829855,0.00002696485,0.00007294269,0.00002569277],"domain_scores_gemma":[0.9998745,0.0000273551,0.00002493479,0.00001141406,0.0000464119,0.00001548192],"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":[0.00006041583,0.00003670666,0.0002905809,0.00007709592,0.00000477084,0.00004286502,0.00001292913,0.0006608145,0.9962921,0.00003079362,0.00002096063,0.002470017],"study_design_scores_gemma":[0.000006281517,0.0002269794,0.003009538,0.000009270209,0.00001038168,0.00004288186,0.00003512555,0.001548316,0.9943973,0.00002357748,0.0006832556,0.000007083295],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937198,0.0004139198,0.004518152,0.00002952455,0.0000087489,0.00005243881,0.0003727792,0.0000280438,0.0008565852],"genre_scores_gemma":[0.9894209,0.0008116186,0.00755167,0.00002827556,0.000004611423,0.00007544874,0.0008413882,0.00003052344,0.001235605],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005649927,"threshold_uncertainty_score":0.001890063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006863989198725682,"score_gpt":0.1856021908954614,"score_spread":0.1787382016967357,"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."}}