{"id":"W3184740927","doi":"10.1016/j.geoderma.2021.115092","title":"Regional soil thickness mapping based on stratified sampling of optimally selected covariates","year":2021,"lang":"en","type":"article","venue":"Geoderma","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Zhejiang University; National Natural Science Foundation of China","keywords":"Topographic Wetness Index; Covariate; Elevation (ballistics); Sampling (signal processing); Statistics; Raster graphics; Soil science; Similarity (geometry); Hydrology (agriculture); Vegetation (pathology); Mesoscale meteorology; Spatial variability; Environmental science; Digital elevation model; Mathematics; Remote sensing; Geology; Geography; Meteorology; Computer science","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":[0.001471539,0.0003669156,0.0007314992,0.0008054264,0.0002149275,0.0003973455,0.0005957726,0.0002291754,0.0009912825],"category_scores_gemma":[0.004535393,0.000275304,0.0005214631,0.0009458141,0.0001559009,0.0002154583,0.0005230815,0.000186862,0.0001943362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002541142,"about_ca_system_score_gemma":0.0008421267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01234881,"about_ca_topic_score_gemma":0.02101565,"domain_scores_codex":[0.9994186,0.0003009997,0.00002265515,0.0001446576,0.00006331188,0.00004987834],"domain_scores_gemma":[0.998849,0.0006044143,0.0001269768,0.000225982,0.0001615396,0.00003209525],"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":[0.002136064,0.0002899987,0.2214718,0.000227939,0.0007811802,0.000341028,0.0005373004,0.4163382,0.05210888,0.006299547,0.003881708,0.2955864],"study_design_scores_gemma":[0.0001750822,0.000152136,0.08494844,0.00001510034,0.000208091,0.0001472211,0.0000787637,0.9006619,0.007096973,0.004903477,0.001572863,0.00004002013],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5677627,0.0002077394,0.4284222,0.0000396813,0.000007910659,0.00009696544,0.001528079,0.001136375,0.0007982274],"genre_scores_gemma":[0.8291988,0.00005988241,0.1684707,0.00001555467,0.000006563308,0.00009839074,0.001750417,0.00006439203,0.0003353624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01234881,"threshold_uncertainty_score":0.02455384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02932945408970918,"score_gpt":0.2435931333187512,"score_spread":0.214263679229042,"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."}}