{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00001687614,0.00008419276,0.0001124036,0.00002820608,0.00005196085,0.00003282874,0.0001328408,0.00006743875,0.0001134629],"category_scores_gemma":[0.00001667364,0.00008699411,0.0000171766,0.00002476634,0.00003789548,0.0002227756,0.00004697001,0.0000255977,0.000002277406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008601868,"about_ca_system_score_gemma":0.000004723047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002062341,"about_ca_topic_score_gemma":0.000002135448,"domain_scores_codex":[0.9996192,0.00000560448,0.00011679,0.0001100534,0.00006726848,0.00008106056],"domain_scores_gemma":[0.9996391,0.00001397811,0.000071674,0.0002063186,0.00002688266,0.00004207359],"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":[0.00000526533,0.000004292694,0.00009359586,0.00001970882,0.00001892056,6.652187e-7,0.00005743133,0.0002424336,0.9964149,0.00004496012,0.000005355379,0.003092483],"study_design_scores_gemma":[0.0001883197,0.000006404848,0.0006438113,0.00002738663,0.00001001481,3.427778e-7,0.000008679725,0.003815776,0.994965,0.00009877047,0.0001457884,0.00008973623],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869478,0.0001285946,0.01224381,0.00003810539,0.0001288143,0.00002075859,0.00001869345,0.00006932089,0.000404051],"genre_scores_gemma":[0.9988643,0.0002927811,0.000620104,0.00001975933,0.00005618627,0.000004157312,0.00007440954,0.00001765779,0.00005067341],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01191642,"threshold_uncertainty_score":0.3547517,"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."}}