{"id":"W2988062336","doi":"10.1039/c9ta11118b","title":"Hydrogen-bonding-induced assembly of aligned cellulose nanofibers into ultrastrong and tough bulk materials","year":2019,"lang":"en","type":"article","venue":"Journal of Materials Chemistry A","topic":"Advanced Cellulose Research Studies","field":"Materials Science","cited_by":145,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Biotech (Canada); University of British Columbia","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Nanofiber; Cellulose; Hydrogen bond; Toughness; Materials science; Polymer; Polymer science; Hydrogen; Molecule; Composite material; Chemical engineering; Polymer chemistry; Nanotechnology; Chemistry; Organic 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001493261,0.0003510154,0.001079012,0.00008303377,0.00009132231,0.0001414353,0.0005022928,0.0001770082,0.002666634],"category_scores_gemma":[0.0002400062,0.0002939173,0.0001068115,0.0001308246,0.0001910254,0.0004705293,0.0002768774,0.00009645755,0.00009824064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001422164,"about_ca_system_score_gemma":0.0001539987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003844104,"about_ca_topic_score_gemma":3.735443e-7,"domain_scores_codex":[0.9968936,0.0001668363,0.001299505,0.0003736023,0.0007217783,0.000544645],"domain_scores_gemma":[0.9974433,0.0002040706,0.00143951,0.0003692429,0.0003218989,0.0002219861],"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":[0.0004242673,0.00008191034,0.00003841985,0.0008860745,0.0000796512,0.00004052102,0.0003383604,0.00001564445,0.9978867,0.00002574081,0.0001436689,0.00003900951],"study_design_scores_gemma":[0.00110381,0.0002398034,0.0000543532,0.0003388551,0.00004810311,0.0001642594,0.0003419683,9.185928e-7,0.9970126,0.0001820328,0.0002483797,0.0002649103],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982028,0.0002629521,0.0000280355,0.0001283386,0.0006432799,0.0002353127,0.00005195981,0.00001908408,0.0004282083],"genre_scores_gemma":[0.9961775,0.0001006001,0.00225512,0.00001358149,0.0003231824,0.000008451206,0.000007041317,0.00004239946,0.001072111],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002568394,"threshold_uncertainty_score":0.9999513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01225776371989327,"score_gpt":0.2682898565026802,"score_spread":0.2560320927827869,"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."}}