{"id":"W4366828140","doi":"10.3390/agronomy13051183","title":"Modeling Topsoil Phosphorus—From Observation-Based Statistical Approach to Land-Use and Soil-Based High-Resolution Mapping","year":2023,"lang":"en","type":"article","venue":"Agronomy","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"State Forest Management Centre; Ministry of Rural Affairs; Eesti Teadusagentuur","keywords":"Topsoil; Environmental science; Soil science; Eutrophication; Biogeochemical cycle; Land use; Soil water; Ecosystem; Phosphorus; Hydrology (agriculture); Nutrient; Ecology; Geology; Environmental chemistry; Chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001457995,0.0001372958,0.0001289437,0.0000371383,0.0001483924,0.00008391879,0.0001174791,0.00005945101,0.00002028459],"category_scores_gemma":[0.00003114672,0.0001304063,0.00002492829,0.0002783185,0.00005211109,0.0001843993,0.00009638373,0.00007891226,0.0001738181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001177029,"about_ca_system_score_gemma":0.000015923,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009449893,"about_ca_topic_score_gemma":0.00004450919,"domain_scores_codex":[0.9988914,0.00003471692,0.0001852034,0.0003949408,0.0002036524,0.0002901253],"domain_scores_gemma":[0.9995095,0.0001200863,0.00002673787,0.0001966755,0.000009128133,0.00013785],"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":[0.00001748573,0.00002940176,0.4723261,0.000004302014,0.000004027712,0.000001501448,0.00009924464,0.5256733,0.00002117218,0.000150681,0.0003664478,0.001306302],"study_design_scores_gemma":[0.0003598702,0.00001364979,0.2345348,0.00001054895,0.000008337918,1.001179e-7,0.00003578857,0.763141,0.00003539011,0.001326656,0.000390192,0.0001437169],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6954529,0.00000474897,0.3038819,0.0002393809,0.00004924285,0.0001362476,0.00004247894,0.00008559853,0.0001075567],"genre_scores_gemma":[0.9543797,0.000002671943,0.04439198,0.0004269532,0.00003065943,0.00006001159,0.0006275433,0.00001590074,0.00006456556],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2594899,"threshold_uncertainty_score":0.9971462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03063536114664473,"score_gpt":0.2071174526157095,"score_spread":0.1764820914690648,"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."}}