{"id":"W4200442616","doi":"10.1016/j.indcrop.2021.114326","title":"Tuning hydrothermal pretreatment severity of wheat straw to match energy application scenarios","year":2021,"lang":"en","type":"article","venue":"Industrial Crops and Products","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Straw; Chemistry; Cellulose; Hemicellulose; Anaerobic digestion; Biofuel; Hydrolysis; Biogas; Fermentation; Enzymatic hydrolysis; Biomass (ecology); Pulp and paper industry; Cellulase; Bioenergy; Agronomy; Food science; Biochemistry; Biotechnology; Waste management; Methane; Organic chemistry; Biology; Inorganic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009675502,0.0001122289,0.0001418749,0.00003919515,0.00005184039,0.00002613825,0.00004864301,0.0001209147,0.00005570556],"category_scores_gemma":[0.00002041632,0.000106349,0.00001997048,0.0002412954,0.00002507192,0.00007217229,0.00003447023,0.0001051269,0.000005548243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003730593,"about_ca_system_score_gemma":0.00004101911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000194616,"about_ca_topic_score_gemma":0.00001239243,"domain_scores_codex":[0.9993049,0.00002786235,0.0001650282,0.0002540101,0.0001103021,0.0001378842],"domain_scores_gemma":[0.9996077,0.000006634649,0.00002568162,0.0002138587,0.00007197585,0.0000741798],"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":[0.0001328264,0.0001320924,0.00183467,0.0002693948,0.00009826521,0.000009149696,0.000576809,0.001410276,0.7338672,0.0002194056,0.008286671,0.2531632],"study_design_scores_gemma":[0.0004977974,0.00007125761,0.0004687452,0.00003552079,0.00002086063,0.0000183776,0.00008594806,0.0007222833,0.872421,0.00003391922,0.1254602,0.0001641055],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946781,0.0006887488,0.0004725326,0.002130055,0.0008003803,0.0003133335,0.00001971543,0.0001039484,0.0007932108],"genre_scores_gemma":[0.9982722,0.00008954656,0.0004872963,0.00004633443,0.0004903841,0.00001120724,0.00002479666,0.00001392879,0.0005642937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2529991,"threshold_uncertainty_score":0.4336788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01947711024499334,"score_gpt":0.2102394585481924,"score_spread":0.190762348303199,"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."}}