{"id":"W3119546722","doi":"10.1007/s10570-020-03618-4","title":"Particle size distributions for cellulose nanocrystals measured by atomic force microscopy: an interlaboratory comparison","year":2021,"lang":"en","type":"article","venue":"Cellulose","topic":"Advanced Cellulose Research Studies","field":"Materials Science","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; McMaster University; National Institute for Nanotechnology; National Research Council Canada","funders":"Natural Resources Canada; National Institute of Standards and Technology","keywords":"Standard deviation; Agglomerate; Asymmetry; Materials science; Particle (ecology); Particle size; Atomic force microscopy; Skew; Particle-size distribution; Analytical Chemistry (journal); Nanotechnology; Statistics; Composite material; Mathematics; Physics; Chemistry; Chromatography","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"],"consensus_categories":[],"category_scores_codex":[0.0007925535,0.0004106761,0.0006559392,0.00003475374,0.000533341,0.0002761366,0.0005314207,0.0001550517,0.0005673912],"category_scores_gemma":[0.001076837,0.000410684,0.0001812806,0.0004610168,0.0004661009,0.0005647936,0.0003175625,0.0002419036,0.0002508616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003748389,"about_ca_system_score_gemma":0.0003679636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000243938,"about_ca_topic_score_gemma":0.00005536127,"domain_scores_codex":[0.9961893,0.0003961756,0.0007342373,0.0009874949,0.0005193074,0.001173482],"domain_scores_gemma":[0.9969419,0.000676566,0.0002472477,0.0008791304,0.000762388,0.0004927621],"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":[0.000151309,0.0005869809,0.000357048,0.0001267916,0.00003500834,0.00002374768,0.0006321569,0.00001261333,0.9859715,0.0007999963,0.01082883,0.0004740829],"study_design_scores_gemma":[0.001206658,0.0002078494,0.00008617284,0.00004724497,0.00005702534,0.000004966286,0.0006704344,0.0008487178,0.9698106,0.001548459,0.02505098,0.0004608748],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9488884,0.007228404,0.04060864,0.000347991,0.0005300638,0.0007300528,0.001270597,0.0002487517,0.0001470691],"genre_scores_gemma":[0.9878823,0.00008834305,0.005716368,0.0001163603,0.0001388906,0.000290984,0.0003331145,0.00007245755,0.005361168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03899388,"threshold_uncertainty_score":0.9998345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02771139295282003,"score_gpt":0.3238359764609832,"score_spread":0.2961245835081631,"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."}}