{"id":"W2793118230","doi":"10.1016/j.powtec.2018.02.008","title":"Influence of primary particle polydispersity and overlapping on soot morphological parameters derived from numerical TEM images","year":2018,"lang":"en","type":"article","venue":"Powder Technology","topic":"Coagulation and Flocculation Studies","field":"Environmental Science","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada","funders":"Comisión Nacional de Investigación Científica y Tecnológica; Universidad Técnica Federico Santa María","keywords":"Soot; Dispersity; Fractal dimension; Materials science; Particle (ecology); Particle size; Aggregate (composite); Particle-size distribution; Primary (astronomy); Fractal; Nanotechnology; Chemistry; Mathematics; Polymer chemistry; Physics; Combustion; Physical chemistry; Mathematical analysis","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":[0.0000498508,0.00008385709,0.0001566188,0.00003278772,0.0001037455,0.000005884521,0.0001021747,0.00008067319,0.0001998288],"category_scores_gemma":[0.00008722246,0.00007215635,0.0000207529,0.0002071058,0.0009607128,0.00006923415,0.0002774322,0.00007857253,0.00009904571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003828138,"about_ca_system_score_gemma":0.000002597194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001602356,"about_ca_topic_score_gemma":0.000009664362,"domain_scores_codex":[0.9993134,0.00002334785,0.0001415856,0.000251814,0.0001181714,0.0001517154],"domain_scores_gemma":[0.9996499,0.00006721276,0.00006206907,0.0001758508,0.00001046947,0.00003453622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002900574,0.00004356643,0.7015883,0.000001017084,0.00001150748,0.000003127646,0.0001521878,0.0001932225,0.2930664,0.0001133065,0.00008991258,0.004708406],"study_design_scores_gemma":[0.0002151124,0.00009454296,0.9640771,0.000004425229,0.000007552871,0.000003740496,0.0001038335,0.0004812136,0.03395458,0.0008287465,0.000146326,0.00008288913],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975004,0.00003379133,0.000640141,0.001170736,0.00001620172,0.00007964888,0.00000485663,0.00008211794,0.0004721494],"genre_scores_gemma":[0.9975567,0.000007756928,0.001952857,0.0004516929,0.000005899634,0.000004572453,0.000001094343,0.000003561257,0.00001583773],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2624887,"threshold_uncertainty_score":0.3539787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01730638273762383,"score_gpt":0.236685249811418,"score_spread":0.2193788670737942,"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."}}