{"id":"W4384824854","doi":"10.32920/23710008","title":"Ozone pretreatment of humid wheat straw for biofuel production","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ozonolysis; Straw; Lignin; Chemistry; Ozone; Hydrolysis; Biofuel; Yield (engineering); Agronomy; Animal science; Food science; Horticulture; Pulp and paper industry; Organic chemistry; Biotechnology; Biology; Materials science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001038313,0.0003951386,0.000250198,0.0001345602,0.000173989,0.0003141398,0.0001556631,0.0002049989,0.001505993],"category_scores_gemma":[0.00006275824,0.0001242204,0.0003011904,0.0001885623,0.00008790427,0.0001484019,0.0002099119,0.0003169275,0.0002853936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001796655,"about_ca_system_score_gemma":0.0002205664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001270736,"about_ca_topic_score_gemma":0.001997594,"domain_scores_codex":[0.9999237,0.000005936598,0.000004260251,0.000020718,0.0000224857,0.00002281774],"domain_scores_gemma":[0.9999803,0.000002557338,0.000004487078,0.000003102227,0.000004612317,0.000004782769],"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":[0.00001580758,0.000005862777,0.00005283504,0.00002099399,0.000002291439,0.00001617882,0.000005160961,0.00008058764,0.9988519,0.00001911559,0.00001307111,0.0009162198],"study_design_scores_gemma":[0.000003022214,0.00006330515,0.001450105,0.00000165169,0.000005158793,0.00002320679,0.000008808723,0.0003201329,0.9971418,0.00001651028,0.0009637384,0.000002637735],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886132,0.0009575184,0.008423933,0.00004829017,0.00006557981,0.00004507209,0.0002790705,0.00006671801,0.001500555],"genre_scores_gemma":[0.9899888,0.0008293675,0.005854588,0.00003334261,0.00001008501,0.00002390387,0.0004173839,0.0000370551,0.002805448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001505993,"threshold_uncertainty_score":0.005038083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04432419190659713,"score_gpt":0.2574379238780494,"score_spread":0.2131137319714523,"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."}}