{"id":"W4389862672","doi":"10.1016/j.biortech.2023.130211","title":"Improved energy recovery from yard waste by water-starved hydrothermal treatment: Effects of process water and pressure","year":2023,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Hydrothermal carbonization; Waste management; Energy recovery; Biomass (ecology); Carbon fibers; Char; Environmental science; Carbonization; Cabin pressurization; Carbon sequestration; Municipal solid waste; Moisture; Hydrothermal circulation; Energy consumption; Pulp and paper industry; Pyrolysis; Materials science; Carbon dioxide; Chemistry; Chemical engineering; Adsorption; Ecology; Engineering; Energy (signal processing)","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00013425,0.0002546403,0.0003790682,0.000179374,0.0001814639,0.0003916585,0.0002610843,0.0003492552,0.0008497714],"category_scores_gemma":[0.0001244327,0.0001431025,0.0003433768,0.0003043677,0.0001437977,0.0003286363,0.0001600552,0.0004799641,0.0002294883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002674943,"about_ca_system_score_gemma":0.0003412404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002046713,"about_ca_topic_score_gemma":0.004119782,"domain_scores_codex":[0.9999212,0.000006073182,0.000009590443,0.00001338039,0.0000242773,0.00002550573],"domain_scores_gemma":[0.9999563,0.000007618994,0.000008895044,0.00000599743,0.000012534,0.000008623],"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":[0.0001599158,0.00002389796,0.0001812194,0.00002541323,0.000005075279,0.00002880669,0.0000101108,0.0002409228,0.9973891,0.00002937174,0.00002371805,0.001882375],"study_design_scores_gemma":[0.000003741982,0.00005699149,0.0009616993,0.000001131081,0.000006132815,0.00002083268,0.00001082047,0.0006447059,0.998108,0.000009025089,0.0001745412,0.000002448067],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979696,0.0002384009,0.00121046,0.00002720289,0.000008183866,0.000003030593,0.00009557801,0.00003285767,0.0004147012],"genre_scores_gemma":[0.9976083,0.0001418528,0.0008675593,0.0000080681,0.000001799308,0.000002492309,0.0001430522,0.00001619011,0.001210699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002046713,"threshold_uncertainty_score":0.004069567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00270503026067177,"score_gpt":0.1688844126890172,"score_spread":0.1661793824283455,"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."}}