{"id":"W2900740092","doi":"10.1016/j.cosust.2018.10.010","title":"Modeling phosphorus in rivers at the global scale: recent successes, remaining challenges, and near-term opportunities","year":2018,"lang":"en","type":"article","venue":"Current Opinion in Environmental Sustainability","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Wageningen University and Research; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Planbureau voor de Leefomgeving; Koninklijke Nederlandse Akademie van Wetenschappen; Svenska Forskningsrådet Formas; Delta; M.S.I. Foundation; Vetenskapsrådet; National Science Foundation","keywords":"Sustainability; Environmental science; Scale (ratio); Global population; Biogeochemical cycle; Term (time); Environmental resource management; Phosphorus; Population; Computer science; Ecology; Geography; Biology","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":[0.000780663,0.0002682655,0.00021316,0.00002725818,0.0003488875,0.00004086208,0.0002977563,0.00009730743,0.0001554856],"category_scores_gemma":[0.00004479573,0.000225282,0.00004578185,0.0001620328,0.00154237,0.000326154,0.001107523,0.0002627166,0.00002090837],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004103163,"about_ca_system_score_gemma":0.0000292097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005535951,"about_ca_topic_score_gemma":0.0002642132,"domain_scores_codex":[0.9976867,0.0002404937,0.0004165328,0.0006899609,0.0003953986,0.0005709586],"domain_scores_gemma":[0.9992939,0.00004709141,0.00007905478,0.0004177883,0.000006916792,0.0001553047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009878618,0.0002211627,0.8333368,0.00004900778,0.000002435394,0.000002294964,0.002201447,0.00139803,5.905761e-7,0.0000661392,0.00002396353,0.1625994],"study_design_scores_gemma":[0.001066898,0.0001352882,0.920984,0.00008236257,0.00000774103,0.00001361879,0.007732803,0.03277342,0.000007004522,0.0133327,0.02343221,0.0004319117],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920725,0.00487901,0.00003965756,0.001219221,0.0007200018,0.0005518539,0.0000259739,0.00002449046,0.0004673075],"genre_scores_gemma":[0.9757054,0.02403935,0.00004097349,0.00002645693,0.00005614559,0.00005565243,0.00004759789,0.00001335692,0.00001501694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1621674,"threshold_uncertainty_score":0.9997199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04195352669424023,"score_gpt":0.2843248299370604,"score_spread":0.2423713032428202,"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."}}