{"id":"W2783557968","doi":"","title":"Effects of Land Use and Hydrophysical Drivers on Temporal and Spatial Variability of Phosphorus and Nitrate Export in an Agricultural Subwatershed in Southern Ontario, Canada","year":2018,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Nitrate; Environmental science; Phosphorus; Agricultural land; Land use; Hydrology (agriculture); Geography; Water resource management; Ecology; Engineering; Civil engineering; Chemistry; Geotechnical engineering; Biology; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008583269,0.0001772271,0.0003555275,0.0000564076,0.0000391892,0.000008366202,0.0001013196,0.0001367813,0.000009728553],"category_scores_gemma":[0.000005317123,0.0001609217,0.00002547076,0.00007956264,0.0002292265,0.0001867859,0.00006428264,0.0001368584,3.617934e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001671059,"about_ca_system_score_gemma":0.00004047199,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.996326,"about_ca_topic_score_gemma":0.9976326,"domain_scores_codex":[0.9991034,0.00006917488,0.0001292015,0.0003367761,0.0002009735,0.0001605126],"domain_scores_gemma":[0.999597,0.00003682712,0.0001514992,0.0001117567,0.00001764877,0.00008522697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004360633,0.0001185862,0.9325976,0.00009545671,0.00001293032,0.00002734536,0.0650101,0.0000225574,0.001463948,9.895971e-7,0.000005243371,0.0002091877],"study_design_scores_gemma":[0.0011938,0.0002999321,0.9845399,0.00009903379,0.00004074383,6.655048e-7,0.0117742,0.0003466746,0.00144998,0.00007885785,0.000002303913,0.0001739001],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996455,0.000003104469,2.881118e-7,0.00001316421,0.00004796573,0.0002373517,0.00003560675,0.000003350958,0.00001372459],"genre_scores_gemma":[0.9980444,0.00001217795,0.00008189981,0.000002264747,0.000003465466,3.236492e-7,0.0001366273,0.000006359654,0.001712537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0532359,"threshold_uncertainty_score":0.6562197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003395901554661185,"score_gpt":0.1509367079431067,"score_spread":0.1475408063884455,"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."}}