{"id":"W3025100529","doi":"10.1520/gtj20190030","title":"Variability in Particle Size Distribution Due to Sampling","year":2020,"lang":"en","type":"article","venue":"Geotechnical Testing Journal","topic":"Cyclone Separators and Fluid Dynamics","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cégep de Saint-Laurent; École de Technologie Supérieure","funders":"","keywords":"Particle-size distribution; Geotechnical engineering; Sampling (signal processing); Geology; Particle (ecology); Distribution (mathematics); Environmental science; Particle size; Soil science; Mathematics; Engineering; 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":[0.0007536032,0.0001106455,0.0001860046,0.000009685437,0.00007384762,0.00006707702,0.0001456682,0.000079062,0.00002145317],"category_scores_gemma":[0.005655292,0.0001116926,0.0000466891,0.0005507631,0.00002095048,0.00008265637,0.00005996066,0.00059275,0.00002093648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001366911,"about_ca_system_score_gemma":0.00002381147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000524078,"about_ca_topic_score_gemma":0.000001601271,"domain_scores_codex":[0.9989471,0.00004319117,0.0003909733,0.0001496359,0.0001432141,0.0003258757],"domain_scores_gemma":[0.999023,0.0004924726,0.00002621745,0.0001117325,0.00004595994,0.0003006051],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002185219,0.00004403483,0.01012987,0.00002726063,0.000008356058,0.00008725681,0.0001023974,0.9361838,0.02941181,0.0003975853,0.0003245932,0.02326125],"study_design_scores_gemma":[0.0002320785,0.00007185288,0.05558623,0.00004610041,0.000007154486,0.0001249085,0.0000105784,0.941171,0.0003248844,0.001416503,0.000822853,0.0001858852],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6016427,0.00001817195,0.3974638,0.0004750164,0.00007078302,0.00006419004,0.00000814303,0.0002016642,0.00005559263],"genre_scores_gemma":[0.9871367,0.000003282192,0.01248916,0.0001481809,0.0001999676,0.000004166998,0.000001768473,0.00001600628,7.426416e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3854941,"threshold_uncertainty_score":0.6770322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03035729759563407,"score_gpt":0.250069469383687,"score_spread":0.2197121717880529,"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."}}