{"id":"W4241423236","doi":"10.26434/chemrxiv.7312070.v2","title":"Synthesis of High Molecular Weight Chitosan from Chitin by Mechanochemistry and Aging","year":2018,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Nanocomposite Films for Food Packaging","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Chitin; Chitosan; Magic angle spinning; Solvent; Viscometer; Chemical engineering; Polymer chemistry; Chemistry; Materials science; Organic chemistry; Nuclear magnetic resonance spectroscopy; Composite material; Viscosity","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":[0.0001370267,0.0004399872,0.0001639414,0.000224578,0.0001462892,0.0002397856,0.0002372588,0.0002821957,0.0009141341],"category_scores_gemma":[0.0001504011,0.0001606843,0.0002268936,0.0001965316,0.0002044441,0.0003147982,0.0002340657,0.0005932751,0.0002518331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002783673,"about_ca_system_score_gemma":0.0002798671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007601246,"about_ca_topic_score_gemma":0.001886583,"domain_scores_codex":[0.9998966,0.000006295196,0.00001002665,0.00002447362,0.00004438084,0.00001816508],"domain_scores_gemma":[0.9998968,0.00001468973,0.00003589347,0.00001455123,0.00002371482,0.00001433468],"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":[0.000004739005,0.000004013198,0.00002307628,0.00003498883,0.000002233536,0.00003146184,0.000006979684,0.0000373381,0.9979025,0.00008024199,0.0000262171,0.001846109],"study_design_scores_gemma":[0.000002873289,0.00004478868,0.00049792,0.00000295446,0.000004423925,0.0001048816,0.000004776885,0.00031198,0.9971283,0.00002237012,0.00187054,0.000004277434],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8707685,0.007022893,0.1106996,0.0005075431,0.0003170499,0.0002839502,0.0003795323,0.000653318,0.009367541],"genre_scores_gemma":[0.9092328,0.003506586,0.07932168,0.0002263987,0.00005505458,0.0001077632,0.0002805972,0.0001229059,0.007146157],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009141341,"threshold_uncertainty_score":0.003058076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005470588416454284,"score_gpt":0.2113497573632406,"score_spread":0.2058791689467863,"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."}}