{"id":"W3174864010","doi":"10.1016/j.jconhyd.2021.103852","title":"Spatiotemporal analysis of land use pattern and stream water quality in southern Alberta, Canada","year":2021,"lang":"en","type":"article","venue":"Journal of Contaminant Hydrology","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Environment and Protected Areas; Concordia University","funders":"National Key Research and Development Program of China; Natural Sciences and Engineering Research Council of Canada","keywords":"Environmental science; Water quality; Land use; Hydrology (agriculture); Surface runoff; Irrigation; Watershed; Grassland; Land use, land-use change and forestry; Agricultural land; Water resource management; Ecology; Geology","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":[0.0003136317,0.0001841105,0.0002260515,0.001716747,0.001053155,0.00106668,0.0006362076,0.0002996278,0.001330228],"category_scores_gemma":[0.000973759,0.0001647339,0.0002773294,0.004950071,0.000490089,0.0002377105,0.0004790351,0.000232668,0.0001608713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01110497,"about_ca_system_score_gemma":0.01190827,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9939758,"about_ca_topic_score_gemma":0.9973795,"domain_scores_codex":[0.9997858,0.00001943919,0.00001592052,0.00004180576,0.00007014675,0.00006670999],"domain_scores_gemma":[0.9991049,0.00009118475,0.0001306333,0.00002898684,0.0005124662,0.0001317456],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000113201,0.00003781662,0.9846666,0.00003312849,0.00008329154,0.0001747356,0.0007014422,0.001645805,0.001067576,0.0002508037,0.001447411,0.009778142],"study_design_scores_gemma":[0.000002645354,0.000004507807,0.9968411,0.000009160416,0.00001496537,0.00002526001,0.0008682843,0.001245953,0.00006249617,0.00002464032,0.0008950583,0.000005956182],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954967,0.0003041461,0.0001399916,0.0001236526,0.000004780051,0.00001252862,0.002682667,0.00001173413,0.00122383],"genre_scores_gemma":[0.9959493,0.0002824371,0.0003242645,0.00002970695,0.000002786846,0.000008648116,0.001798923,0.000005152097,0.001598885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01110497,"threshold_uncertainty_score":0.08057261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01564587106145814,"score_gpt":0.2526291916076792,"score_spread":0.236983320546221,"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."}}