{"id":"W4408245256","doi":"10.1002/cssc.202500329","title":"Advanced Characterization of Lignin Nanoparticles by Asymmetric Flow‐Field Flow Fractionation","year":2025,"lang":"en","type":"article","venue":"ChemSusChem","topic":"Field-Flow Fractionation Techniques","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Dynamic light scattering; Dispersity; Field flow fractionation; Characterization (materials science); Multiangle light scattering; Light scattering; Nanoparticle; Particle (ecology); Scattering; Particle size; Materials science; Nanotechnology; Particle-size distribution; Chemistry; Fractionation; Optics; Polymer chemistry; Chromatography; Physics; Physical chemistry; Geology","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":[],"consensus_categories":[],"category_scores_codex":[0.0001121809,0.000126621,0.0001577794,0.0002411321,0.00005034549,0.00001424567,0.0001063806,0.0001842184,0.00007682923],"category_scores_gemma":[0.0002099312,0.0001493227,0.00004745353,0.0006937205,0.00001412823,0.0003486851,0.00002054935,0.0001858531,0.00001740449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001024138,"about_ca_system_score_gemma":0.00002204283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004215744,"about_ca_topic_score_gemma":0.000001244189,"domain_scores_codex":[0.9991953,0.00001461238,0.000326128,0.0001558614,0.0001659907,0.0001420566],"domain_scores_gemma":[0.9994028,0.0001564566,0.00007188378,0.0001814213,0.0001578126,0.00002965635],"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":[0.000008939659,0.00003208891,0.0002485834,0.000081062,0.00002677176,1.740756e-7,0.00004050169,0.0002493753,0.9161456,0.0002106954,0.01651674,0.0664395],"study_design_scores_gemma":[0.000239773,0.00001692221,0.000940846,0.00003914211,0.00001122413,3.338489e-7,0.00002485812,0.02679407,0.9480845,0.0001755858,0.0235565,0.000116211],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7705452,0.0004392014,0.1900465,0.00088582,0.001251615,0.0005424484,0.00004529585,0.001384996,0.03485892],"genre_scores_gemma":[0.9921257,0.0001699185,0.006564653,0.00015243,0.00005030253,0.00008018839,0.0001444661,0.0000207898,0.0006915394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2215805,"threshold_uncertainty_score":0.6089205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003357917584315828,"score_gpt":0.2117237339734049,"score_spread":0.2083658163890891,"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."}}