{"id":"W3093399447","doi":"10.1016/j.jenvman.2020.111427","title":"A comparative evaluation of the continuous and event-based modelling approaches for identifying critical source areas for sediment and phosphorus losses","year":2020,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of the Environment, Conservation and Parks; University of Guelph","funders":"Ministère de l’Environnement, de la Protection de la nature et des Parcs","keywords":"Watershed; Soil and Water Assessment Tool; Environmental science; SWAT model; Nonpoint source pollution; Surface runoff; Hydrology (agriculture); Sediment; Water quality; Watershed management; Streamflow; Drainage basin; Ecology; Geography; Geology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000700658,0.0001306568,0.0002381918,0.00002039584,0.0001888951,0.00002016275,0.0001261003,0.00002751471,0.00002886013],"category_scores_gemma":[0.00001937032,0.00009672246,0.00009032671,0.00003809598,0.0003232083,0.0001286343,0.0002206087,0.00006490041,0.000001033186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000796602,"about_ca_system_score_gemma":0.000002598293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002592807,"about_ca_topic_score_gemma":8.018685e-7,"domain_scores_codex":[0.9988495,0.00007566284,0.0003312965,0.0002050411,0.0003821226,0.0001564096],"domain_scores_gemma":[0.9995134,0.0001061962,0.0002343817,0.00007894691,0.00000656388,0.00006052217],"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":[0.0008851108,0.0006461367,0.02830786,0.0003932985,0.0006798976,0.000003492492,0.004585599,0.9424763,0.001067215,0.0004830162,0.001264911,0.01920712],"study_design_scores_gemma":[0.004412008,0.0008747168,0.02864022,0.0001035111,0.00175951,0.000005180613,0.007416252,0.9458651,0.004011341,0.003048104,0.003588727,0.0002753252],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8282949,0.0009194665,0.1671422,0.002209303,0.00007620023,0.001208626,0.00001198632,0.000003532678,0.0001337885],"genre_scores_gemma":[0.9954526,0.00007179783,0.004040611,0.0003092927,0.00002249472,0.0000579286,0.000001701616,0.000008186854,0.00003534902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1671578,"threshold_uncertainty_score":0.3944227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08779192502715814,"score_gpt":0.285087825974273,"score_spread":0.1972959009471149,"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."}}