{"id":"W4389482862","doi":"10.1016/j.rsase.2023.101123","title":"Multi-property digital soil mapping at 30-m spatial resolution down to 1 m using extreme gradient boosting tree model and environmental covariates","year":2023,"lang":"en","type":"article","venue":"Remote Sensing Applications Society and Environment","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"University of Tabriz; University of Guelph","keywords":"Digital soil mapping; Covariate; Soil horizon; Environmental science; Terrain; Soil science; Spatial variability; Soil map; Mathematics; Statistics; Geography; Soil water; Cartography","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":[0.0006564082,0.0003122893,0.0005355028,0.000577494,0.000265398,0.0003547549,0.0008731156,0.000494213,0.001242885],"category_scores_gemma":[0.001095026,0.0003133191,0.0007408956,0.0009298987,0.0002149228,0.0005111853,0.0006000772,0.000511945,0.0004188747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002468986,"about_ca_system_score_gemma":0.0006438939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009722056,"about_ca_topic_score_gemma":0.01660736,"domain_scores_codex":[0.9998084,0.00004216,0.000008188967,0.0000640935,0.00004400786,0.00003320026],"domain_scores_gemma":[0.9997124,0.000086669,0.00003013794,0.00007022125,0.00007964155,0.00002087456],"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":[0.0003255358,0.0003393723,0.01877237,0.0001133703,0.0002012537,0.0001618892,0.00009995268,0.7717643,0.01851232,0.00295399,0.003307615,0.1834481],"study_design_scores_gemma":[0.000006821988,0.00001162749,0.002941015,0.000002457195,0.00001204453,0.00001732063,0.000008045445,0.9947947,0.0009516983,0.0007486478,0.0004995688,0.000006119065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4086435,0.0003304168,0.5856911,0.0001986227,0.00005506309,0.00004532702,0.001636952,0.001825438,0.001573686],"genre_scores_gemma":[0.8314729,0.00009491316,0.164416,0.00004097649,0.00001958831,0.00003607445,0.00229746,0.00007918706,0.001542847],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009722056,"threshold_uncertainty_score":0.01933092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03787955163416522,"score_gpt":0.2200958343859541,"score_spread":0.1822162827517889,"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."}}