{"id":"W4210766546","doi":"10.1002/ceat.202100517","title":"Extraction of Sugars and Cellulose Fibers from <i>Cannabis</i> Stems by Hydrolysis, Pulping, and Bleaching","year":2022,"lang":"en","type":"article","venue":"Chemical Engineering & Technology","topic":"Lignin and Wood Chemistry","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Department of Science and Technology, Ministry of Science and Technology, India","keywords":"Hemicellulose; Cellulose; Lignin; Chemistry; Hydrolysis; Crystallinity; Extraction (chemistry); Yield (engineering); Thermal stability; Nuclear chemistry; Chromatography; Organic chemistry; Materials science; Composite material","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":[0.00008557786,0.0005201664,0.0002273258,0.0004081676,0.000296675,0.0002254331,0.0001382187,0.0001505716,0.0008163627],"category_scores_gemma":[0.00009010476,0.0001579355,0.0003324201,0.0003140566,0.0002002661,0.0002443465,0.0001436415,0.0003826801,0.000195872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002352098,"about_ca_system_score_gemma":0.0003221667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00213114,"about_ca_topic_score_gemma":0.004285802,"domain_scores_codex":[0.999946,0.000005142959,0.000003700627,0.00001297367,0.00001811909,0.00001400959],"domain_scores_gemma":[0.9999522,0.000006118436,0.00001249635,0.000004453138,0.00001074463,0.00001393017],"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":[0.00004312427,0.00000549218,0.0001423287,0.00003444096,0.000004458026,0.00003699761,0.000008293207,0.00005112818,0.9987337,0.00002564649,0.000008993154,0.0009054837],"study_design_scores_gemma":[0.000003218675,0.00004975841,0.004302672,0.000006897944,0.00001435499,0.00006715409,0.00001675233,0.0002989502,0.9945332,0.00002881515,0.0006700986,0.000008157063],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931583,0.0008278587,0.003077608,0.00002734184,0.00001187861,0.00004398228,0.0003393335,0.00004338314,0.002470414],"genre_scores_gemma":[0.9911248,0.0006514056,0.005601414,0.00002483842,0.000008454506,0.00002967479,0.0005852048,0.00003544366,0.001938644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00213114,"threshold_uncertainty_score":0.004237533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.001686976667478158,"score_gpt":0.1577686382092594,"score_spread":0.1560816615417812,"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."}}