{"id":"W4389347213","doi":"10.1016/j.pedsph.2023.12.004","title":"Comparing disaggregation approaches DSMART and PPD in disaggregating soil series maps","year":2023,"lang":"en","type":"article","venue":"Pedosphere","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University; University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Agriculture, Food and Rural Affairs","keywords":"Polygon (computer graphics); Latin hypercube sampling; Sampling (signal processing); Series (stratigraphy); Sample (material); Statistics; Mathematics; Simple random sample; Sample size determination; Algorithm; Computer science; Set (abstract data type); Monte Carlo method; Geology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003024786,0.000559611,0.0007652303,0.002134998,0.000358848,0.002049211,0.0006647842,0.0006647006,0.002216981],"category_scores_gemma":[0.01170885,0.0004422267,0.0008952087,0.002849541,0.0003251115,0.001626651,0.001356658,0.0005754695,0.0004983373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008495176,"about_ca_system_score_gemma":0.0009493735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03476664,"about_ca_topic_score_gemma":0.03812491,"domain_scores_codex":[0.9987937,0.0005653189,0.0001120551,0.0001612484,0.0002562135,0.0001114075],"domain_scores_gemma":[0.9936023,0.004286029,0.0002093414,0.001037934,0.0007454717,0.0001188839],"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":[0.002070045,0.000305315,0.04280933,0.0005816665,0.001003849,0.0001368119,0.0007074939,0.6264984,0.006565292,0.01255495,0.00566312,0.3011037],"study_design_scores_gemma":[0.00009692791,0.0001196158,0.03370055,0.00004743011,0.0002007614,0.00006431428,0.000525735,0.9516864,0.002703834,0.005900286,0.004899936,0.00005407909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7668384,0.00176338,0.2083369,0.0007826816,0.0001454719,0.0002220306,0.009831694,0.003330274,0.008749312],"genre_scores_gemma":[0.8724275,0.0005538253,0.1200096,0.0001511693,0.00004163354,0.00009627675,0.005300378,0.000369379,0.001050396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03476664,"threshold_uncertainty_score":0.06912857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03780175176220089,"score_gpt":0.2227828753697923,"score_spread":0.1849811236075914,"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."}}