{"id":"W2009599084","doi":"10.1557/opl.2011.132","title":"Process Optimization for Nanocrystalline Cellulose Production from Microcrystalline Cellulose","year":2011,"lang":"en","type":"article","venue":"MRS Proceedings","topic":"Advanced Cellulose Research Studies","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Institute for Nanotechnology; University of Alberta","funders":"University of Alberta","keywords":"Microcrystalline cellulose; Materials science; Thermogravimetric analysis; Cellulose; Nanocrystalline material; Scanning electron microscope; Chemical engineering; Microcrystalline; Sulfuric acid; Suspension (topology); Composite material; Nanotechnology; Crystallography; Metallurgy; Chemistry","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":[0.0004512024,0.0006004061,0.0007672065,0.0004416542,0.0003939461,0.0009127751,0.0004165952,0.000349679,0.001068999],"category_scores_gemma":[0.0006257888,0.0002885853,0.0005420803,0.0009486109,0.0002135715,0.0004848666,0.0003116689,0.0005946737,0.0003411482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007089691,"about_ca_system_score_gemma":0.0007270343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002543336,"about_ca_topic_score_gemma":0.005178794,"domain_scores_codex":[0.999597,0.00005093584,0.00004663298,0.00009236387,0.0001415484,0.00007149964],"domain_scores_gemma":[0.9998304,0.0000657535,0.00003838672,0.00001929329,0.00003406731,0.0000120916],"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":[0.0003668319,0.0001671383,0.0002335266,0.000158931,0.00001955624,0.00007182044,0.00003618115,0.002906076,0.9839243,0.0001133008,0.00008725626,0.01191515],"study_design_scores_gemma":[0.00001697442,0.0002431166,0.0008043465,0.000004205986,0.0000252467,0.00003137547,0.00002059393,0.003655244,0.9943662,0.00004691617,0.0007759892,0.000009861935],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9765446,0.002723003,0.0175091,0.0001118311,0.00004717907,0.0001075942,0.0003903079,0.0001526261,0.002413705],"genre_scores_gemma":[0.9711825,0.00222482,0.02435501,0.00003901386,0.0000172396,0.00008815779,0.0004468167,0.00007940844,0.001567064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002543336,"threshold_uncertainty_score":0.00514394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03356541454285697,"score_gpt":0.2728622598964852,"score_spread":0.2392968453536282,"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."}}