{"id":"W2910904903","doi":"10.1016/j.dib.2019.01.018","title":"Bioenergy production data from anaerobic digestion of thermally hydrolyzed organic fraction of municipal solid waste","year":2019,"lang":"en","type":"article","venue":"Data in Brief","topic":"Anaerobic Digestion and Biogas Production","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Greenfield Research (Canada); Toronto Metropolitan University","funders":"Ontario Water Consortium","keywords":"Biogas; Anaerobic digestion; Mesophile; Bioenergy; Methane; Thermal hydrolysis; Chemistry; Municipal solid waste; Hydrolysis; Volume (thermodynamics); Waste management; Pulp and paper industry; Environmental science; Food waste; Biodegradable waste; Biofuel; Organic chemistry; Environmental engineering; Sewage treatment; Engineering","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":[0.0003665631,0.0001442747,0.000267777,0.0001482808,0.00001797145,0.00001372006,0.0006810505,0.0001116042,0.0002177722],"category_scores_gemma":[0.0001170012,0.000147659,0.00001853077,0.0003610358,0.00004834197,0.001027601,0.0002665565,0.0001627073,0.00003743752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004806104,"about_ca_system_score_gemma":0.00002755356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001609172,"about_ca_topic_score_gemma":0.0004693686,"domain_scores_codex":[0.9986828,0.0000533971,0.0004391706,0.0004587992,0.0002053948,0.0001604573],"domain_scores_gemma":[0.9976093,0.00002538954,0.0001569432,0.002128353,0.00004902369,0.00003099375],"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":[0.0001049699,0.0002074738,0.004889957,0.00006814969,0.0001047844,0.00000134355,0.0001903304,0.02235595,0.9638961,0.0003338327,0.001885336,0.005961799],"study_design_scores_gemma":[0.002731096,0.000261886,0.09082748,0.0006867741,0.0002214118,0.00001964973,0.001279976,0.2115503,0.6556148,0.0002858324,0.03548126,0.001039581],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974189,0.0001971383,0.0006198162,0.00009254264,0.000804031,0.0002040139,0.0004306949,0.00008989292,0.000143017],"genre_scores_gemma":[0.9895506,0.0004379606,0.0006343234,0.00001101472,0.0001896475,0.000002417021,0.009097599,0.00002820194,0.00004823795],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3082813,"threshold_uncertainty_score":0.6021358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02619237254353228,"score_gpt":0.2498107950711766,"score_spread":0.2236184225276443,"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."}}