{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005444431,0.0001648136,0.0002318996,0.0000954996,0.00003110012,0.00000952763,0.0001435798,0.0001780331,0.00001176689],"category_scores_gemma":[0.00001882868,0.0002038858,0.00002956858,0.0001894178,0.00005537144,0.00004674503,0.0001325302,0.0005274868,4.287371e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007143086,"about_ca_system_score_gemma":0.000004678897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002924379,"about_ca_topic_score_gemma":1.362876e-7,"domain_scores_codex":[0.9992357,0.00000353767,0.0002086715,0.0002311114,0.0001017842,0.000219175],"domain_scores_gemma":[0.9996765,0.00003590391,0.00003573187,0.0001826129,0.000007309846,0.00006199978],"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":[0.000001652364,0.00001302176,0.0001259633,0.00007754711,0.00004600905,0.000004017823,0.00006341404,0.001536227,0.995086,0.000031059,0.002138592,0.0008764603],"study_design_scores_gemma":[0.0002349204,0.00001382761,0.000004307473,0.00001759107,0.00002387818,0.00002543121,0.00007138274,0.02238872,0.9685388,0.00008190637,0.00841032,0.0001889274],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944597,0.004043943,0.000557685,0.0001114821,0.0001076866,0.00005612319,0.00003165051,0.0005136362,0.0001180796],"genre_scores_gemma":[0.9988732,0.0000747528,0.0008624652,0.000009178871,0.00002598551,0.00003486151,0.00003578242,0.00003826836,0.00004546762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02654725,"threshold_uncertainty_score":0.8314222,"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."}}