{"id":"W2942575235","doi":"10.15376/biores.14.2.3808-3822","title":"The feasibility of shortening the pretreatment time for improvement of the biogas production rate from rice straw with three chemical agents","year":2019,"lang":"en","type":"article","venue":"BioResources","topic":"Anaerobic Digestion and Biogas Production","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Agriculture","funders":"","keywords":"Straw; Biogas; Rice straw; Distilled water; Chemistry; Methane; Anaerobic digestion; Biogas production; Yield (engineering); Bioenergy; Pulp and paper industry; Nuclear chemistry; Animal science; Agronomy; Materials science; Waste management; Biofuel; Biotechnology; Biology; Chromatography; Organic chemistry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002203014,0.0007159113,0.0003603057,0.0002208629,0.0001755823,0.0002418901,0.0002713449,0.0003473508,0.0006641219],"category_scores_gemma":[0.0001882205,0.0001664287,0.0004061869,0.0003190502,0.0001863123,0.0003740705,0.0001655503,0.0004378569,0.0001358147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002783174,"about_ca_system_score_gemma":0.0006155965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001562966,"about_ca_topic_score_gemma":0.003704385,"domain_scores_codex":[0.9998748,0.00001535058,0.00001348266,0.00003077275,0.00003574634,0.00002975245],"domain_scores_gemma":[0.9999225,0.00001051465,0.00002569333,0.000008023371,0.00002215905,0.00001103389],"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":[0.00004712373,0.00001196619,0.0001036047,0.00004748346,0.000002462083,0.00001090093,0.000004280522,0.00007852895,0.9986129,0.00002143824,0.000007072966,0.00105212],"study_design_scores_gemma":[0.000008574518,0.0001904161,0.001453828,0.000002580335,0.0000156363,0.0000244708,0.0000146139,0.0006266584,0.9969918,0.00001956531,0.0006464524,0.00000535237],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9849141,0.001454976,0.01244374,0.0001107038,0.00006030363,0.0000521136,0.0001591117,0.00007420063,0.0007306165],"genre_scores_gemma":[0.9784974,0.001100788,0.01884041,0.00004411686,0.00001174578,0.00005957557,0.0002848555,0.00001822154,0.001142915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001562966,"threshold_uncertainty_score":0.003107727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01305399344136272,"score_gpt":0.2075085852642532,"score_spread":0.1944545918228905,"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."}}