{"id":"W4366774243","doi":"10.2139/ssrn.4425542","title":"Geospatial Modelling of Soil Phosphorus Fractions and Sorption Indicators from Heterogeneous Landscapes","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Aqua regia; Sorption; Environmental science; Phosphorus; Geological survey; Scale (ratio); Geologic map; Soil map; Geostatistics; Hydrology (agriculture); Environmental chemistry; Soil water; Soil science; Geology; Chemistry; Spatial variability; Geography; Geomorphology; Cartography","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":[0.000328004,0.0004731714,0.0005049731,0.000572528,0.0003515652,0.00128995,0.0009283738,0.001064109,0.001091462],"category_scores_gemma":[0.00144276,0.0005108913,0.0006760464,0.001208759,0.0006766536,0.0009418435,0.000691302,0.0005009441,0.0001064198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00108941,"about_ca_system_score_gemma":0.0008061976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06927123,"about_ca_topic_score_gemma":0.04447093,"domain_scores_codex":[0.9998744,0.00003749768,0.000008499522,0.00003947674,0.00001807194,0.00002212874],"domain_scores_gemma":[0.9995738,0.000272654,0.00005314008,0.00002750319,0.0000406374,0.00003232402],"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":[0.00001665108,0.00001784327,0.001314403,0.000008412774,0.0000134214,0.00002409481,0.000008219626,0.9963982,0.0004298221,0.0007635858,0.00006160306,0.0009435605],"study_design_scores_gemma":[0.000002934197,0.000002212855,0.0003808868,5.222728e-7,0.000001863595,0.000002521728,0.000003826009,0.9991724,0.00006761563,0.0003347129,0.00002889534,0.000001661904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9381081,0.0003006813,0.05733621,0.0003191388,0.00002265174,0.0000273802,0.001013826,0.0003061545,0.002565691],"genre_scores_gemma":[0.9944234,0.0001321622,0.004371913,0.00001319665,0.00000808053,0.00001661766,0.0003113608,0.00003517394,0.000688097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06927123,"threshold_uncertainty_score":0.1377361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01144786122572865,"score_gpt":0.2104961374121634,"score_spread":0.1990482761864348,"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."}}