{"id":"W4293240790","doi":"10.2110/jsr.2021.091","title":"Analysis of common pre-treatments in grain-size analysis (using a grain-size standard)","year":2022,"lang":"en","type":"article","venue":"Journal of Sedimentary Research","topic":"Geology and Paleoclimatology Research","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Silt; Grain size; Particle-size distribution; Sediment; Mineralogy; Sample size determination; Geology; Soil science; Sedimentary depositional environment; Sedimentary rock; Environmental science; Statistics; Mathematics; Particle size; Geomorphology; Paleontology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003623816,0.000642585,0.0008963972,0.0006633243,0.0006664806,0.0009732122,0.001146361,0.0007437741,0.001533458],"category_scores_gemma":[0.006495733,0.000323988,0.001018055,0.0008538312,0.00084143,0.0005588892,0.0008177026,0.001021731,0.0005185058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001155238,"about_ca_system_score_gemma":0.0005481497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001306202,"about_ca_topic_score_gemma":0.002246053,"domain_scores_codex":[0.9936772,0.00121397,0.0006405485,0.001899277,0.002224231,0.000344744],"domain_scores_gemma":[0.9914246,0.003188605,0.00122801,0.001963075,0.002016447,0.0001793371],"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":[0.002805441,0.0009475008,0.02547482,0.0005335961,0.0002785737,0.0001196143,0.0003071614,0.00773488,0.9076282,0.0007811721,0.0005133618,0.05287564],"study_design_scores_gemma":[0.00004772614,0.004206319,0.07966676,0.00004224404,0.0002603473,0.0000878644,0.0001589417,0.01416121,0.8941642,0.0007135913,0.006420035,0.00007075193],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.886115,0.0008648483,0.1069437,0.00007822173,0.0003366876,0.001120687,0.001777965,0.0007139937,0.002048866],"genre_scores_gemma":[0.9104998,0.0003414113,0.08104043,0.0001359604,0.00002834721,0.002743414,0.00288955,0.000460621,0.001860537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003623816,"threshold_uncertainty_score":0.0191648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04491049863643826,"score_gpt":0.3564737641192652,"score_spread":0.3115632654828269,"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."}}