{"id":"W2034642190","doi":"10.1007/s10570-013-0158-2","title":"Preparation and characterization of nanocrystalline cellulose via low-intensity ultrasonic-assisted sulfuric acid hydrolysis","year":2013,"lang":"en","type":"article","venue":"Cellulose","topic":"Advanced Cellulose Research Studies","field":"Materials Science","cited_by":292,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Materials science; Nanocrystalline material; Crystallinity; Thermogravimetric analysis; Hydrolysis; Sulfuric acid; Cellulose; Scanning electron microscope; Acid hydrolysis; Particle size; Crystallite; Ultrasonic sensor; Analytical Chemistry (journal); Chemical engineering; Nuclear chemistry; Composite material; Chromatography; Chemistry; Organic chemistry; Nanotechnology","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":[0.0003912121,0.0003179187,0.0005540178,0.0001686328,0.0001719728,0.00009279689,0.0002526009,0.0001346588,0.0007746859],"category_scores_gemma":[0.0001682267,0.0002817471,0.00009904281,0.0004171126,0.0003719555,0.0007437854,0.0002246294,0.000154213,0.0002922491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001037546,"about_ca_system_score_gemma":0.00005300251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009333566,"about_ca_topic_score_gemma":0.0000127081,"domain_scores_codex":[0.9975231,0.0001663047,0.0006404989,0.0006290333,0.0005063783,0.0005347315],"domain_scores_gemma":[0.9982054,0.0001255474,0.0004094418,0.0005082426,0.000540535,0.0002108573],"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":[0.0001061622,0.0002023593,0.0002836125,0.0001833075,0.00002823464,0.000007757307,0.0005103521,0.00001225174,0.9966817,0.00003456191,0.00006207645,0.001887601],"study_design_scores_gemma":[0.0004813569,0.0001717966,0.01100999,0.00005381283,0.00004177201,0.00001256437,0.00005410781,0.003686144,0.9838327,0.0002112346,0.000166939,0.0002776118],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905598,0.0003943799,0.007556553,0.0001535257,0.0001715575,0.0007777722,0.00002882385,0.0001218475,0.0002357964],"genre_scores_gemma":[0.9962898,0.0002750928,0.001316945,0.00004032842,0.00008711981,0.00009535818,0.0001372541,0.00003553109,0.0017225],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01284905,"threshold_uncertainty_score":0.9999635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01112686321563636,"score_gpt":0.2486723262609414,"score_spread":0.237545463045305,"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."}}