{"id":"W4248114822","doi":"10.26434/chemrxiv.7312070","title":"Synthesis of High Molecular Weight Chitosan from Chitin by Mechanochemistry and Aging","year":2018,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Dyeing and Modifying Textile Fibers","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Chitin; Chitosan; Depolymerization; Magic angle spinning; Chemistry; Chemical engineering; Solvent; Acetylation; Polymer chemistry; Organic chemistry; Materials science; Biochemistry; Nuclear magnetic resonance spectroscopy; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006718479,0.0003531123,0.0004663251,0.00005837889,0.00003045016,0.00003824012,0.0003222082,0.0003920964,0.00006715285],"category_scores_gemma":[0.00005034536,0.0004013063,0.0001088091,0.00005191268,0.000111305,0.00002184099,0.0002750712,0.0003796195,0.000005134749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002646031,"about_ca_system_score_gemma":0.00001920118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008772877,"about_ca_topic_score_gemma":4.149021e-7,"domain_scores_codex":[0.9988267,0.00001488839,0.0002770705,0.0004529189,0.0001688779,0.0002595337],"domain_scores_gemma":[0.9990847,0.00006738663,0.00009853447,0.0006174729,0.00001828352,0.0001136614],"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":[0.000004283959,0.00001951611,0.00006423423,0.0008771181,0.0003219203,0.000008868415,0.0002042777,0.0004052579,0.9924705,0.00002293102,0.002400721,0.00320036],"study_design_scores_gemma":[0.0001260704,0.000003359454,0.00005487167,0.0006995909,0.0001122314,0.000001700977,0.00001306997,0.00220302,0.9949324,0.001237297,0.0002384701,0.0003779673],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909533,0.001660896,0.003170542,0.00005574801,0.0004244885,0.00008490652,0.00009355472,0.0003401359,0.003216408],"genre_scores_gemma":[0.9955346,0.000268072,0.00366903,0.00001510776,0.0002107087,0.00003809294,0.0001352789,0.00009424342,0.00003487314],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004581274,"threshold_uncertainty_score":0.9998439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00503844087535225,"score_gpt":0.1860831556162458,"score_spread":0.1810447147408935,"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."}}