{"id":"W4387446385","doi":"10.1007/s10661-023-11913-3","title":"Runoff, sediment, organic carbon, and nutrient loads from a Canadian prairie micro-watershed under climate variability and land management practices","year":2023,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Agriculture and Agri-Food Canada; Environment and Climate Change Canada","keywords":"Environmental science; Surface runoff; Snowmelt; Hydrology (agriculture); Total suspended solids; Water quality; Watershed; Sediment; Particulates; Nutrient; Suspended solids; Phosphorus; Environmental engineering; Ecology; Chemical oxygen demand; Geology; Sewage treatment","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002382771,0.000277739,0.0001824329,0.0008641388,0.00105194,0.0005630543,0.0005181336,0.0002055663,0.0004560619],"category_scores_gemma":[0.0004296731,0.0001869923,0.0001962975,0.002355515,0.0005048133,0.0002434354,0.0003520517,0.0002449705,0.00006751784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01067966,"about_ca_system_score_gemma":0.007017595,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9759999,"about_ca_topic_score_gemma":0.9925041,"domain_scores_codex":[0.999763,0.00001959236,0.00001082884,0.00005421834,0.00007863184,0.00007372617],"domain_scores_gemma":[0.9997521,0.00002054466,0.00004427344,0.000009947564,0.0001115257,0.0000615887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008653853,0.0001201583,0.9836393,0.00003478075,0.00008579051,0.0002967289,0.000903844,0.001977143,0.003248975,0.00008731363,0.0004308091,0.00908859],"study_design_scores_gemma":[0.000002213258,0.00001362962,0.9979525,0.000001966441,0.000009406807,0.00002362009,0.0005477482,0.001067979,0.0001263997,0.00001293166,0.0002376942,0.000004009137],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991486,0.0000217937,0.00005680015,0.00001363876,4.961275e-7,0.00001573208,0.0005252201,0.000003574602,0.0002139812],"genre_scores_gemma":[0.9976916,0.00008887269,0.000380498,0.00001184794,0.000001248913,0.00001455066,0.00124803,0.000001857862,0.0005613238],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02400011,"threshold_uncertainty_score":0.07748675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0105224923902076,"score_gpt":0.2448731642342059,"score_spread":0.2343506718439983,"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."}}