{"id":"W2889804329","doi":"10.3389/feart.2018.00135","title":"Components of Phosphorus Loss From Agricultural Landscapes, and How to Incorporate Them Into Risk Assessment Tools","year":2018,"lang":"en","type":"article","venue":"Frontiers in Earth Science","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"Environmental science; Cladophora; Surface runoff; Eutrophication; Phosphorus; Manure; Algal bloom; Vegetation (pathology); Agriculture; Environmental engineering; Algae; Nutrient; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004239703,0.0001313069,0.0001830944,0.00005660943,0.0001881772,0.0001119828,0.0004692186,0.00004026366,0.00001446075],"category_scores_gemma":[0.00004157031,0.00009619229,0.00002154603,0.000717076,0.0008909312,0.0006001391,0.0004165243,0.000103268,0.00002930151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009026085,"about_ca_system_score_gemma":0.00001594479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009276383,"about_ca_topic_score_gemma":0.0001184113,"domain_scores_codex":[0.9985631,0.00004022616,0.0001528421,0.0004453554,0.0004911105,0.0003074166],"domain_scores_gemma":[0.9994371,0.00002128696,0.0001190279,0.0002293993,0.00002670529,0.0001664792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001925287,0.00004094606,0.9867913,0.00000116967,0.000003073203,0.000002204076,0.0008009864,0.0001071755,0.001604275,0.00001410241,0.0005115685,0.01010392],"study_design_scores_gemma":[0.0003852993,0.0000930996,0.983637,0.00002005021,0.000004980015,0.000001349173,0.0003613219,0.007608382,0.003204162,0.003212242,0.001318652,0.0001534795],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954033,0.00002261566,0.002806567,0.0002421808,0.0005649353,0.0001795466,0.00003100175,0.00001467619,0.0007351557],"genre_scores_gemma":[0.938374,0.00005222291,0.06141723,0.00005634973,0.00002600799,0.000005793497,0.000008431179,0.000004186534,0.00005577486],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05861066,"threshold_uncertainty_score":0.3922608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008508267180796338,"score_gpt":0.203436668747132,"score_spread":0.1949284015663356,"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."}}