{"id":"W4200482452","doi":"10.1016/j.scitotenv.2021.152362","title":"A statistical framework for testing impacts of multiple drivers of surface water quality in nearshore regions of large lakes","year":2021,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Aquatic Invertebrate Ecology and Behavior","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto and Region Conservation Authority; University of Windsor","funders":"Mitacs","keywords":"Environmental science; Water quality; Hydrology (agriculture); Shore; Benthic zone; Tributary; Surface runoff; Pollution; Oceanography; Ecology; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.07517272,0.001286019,0.002298591,0.003345952,0.002331211,0.003720775,0.004226872,0.002208125,0.003295557],"category_scores_gemma":[0.1453756,0.0008918173,0.003560937,0.002949565,0.006619345,0.003124739,0.00499989,0.00317923,0.0002039825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001977222,"about_ca_system_score_gemma":0.005480431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01533457,"about_ca_topic_score_gemma":0.01166268,"domain_scores_codex":[0.9258782,0.06089234,0.001810928,0.006009995,0.00368259,0.001725982],"domain_scores_gemma":[0.6336128,0.3440948,0.008186845,0.008051392,0.003578502,0.0024756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001512192,0.001264806,0.3119996,0.0004717858,0.006459417,0.002278073,0.002083408,0.1957533,0.004652116,0.3428689,0.003646871,0.1270094],"study_design_scores_gemma":[0.0003416294,0.001785692,0.06328345,0.00008867317,0.00075564,0.0004521972,0.001432145,0.7615366,0.0009592104,0.1669921,0.002237218,0.0001354973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2403473,0.0005374321,0.7536114,0.001338492,0.0001387094,0.0004610946,0.000807139,0.0004497026,0.002308804],"genre_scores_gemma":[0.8587986,0.0001425573,0.1375845,0.0002525594,0.0002176855,0.001178205,0.0005677751,0.00005408249,0.001204067],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07517272,"threshold_uncertainty_score":0.3975561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03028998988067768,"score_gpt":0.2835070770788326,"score_spread":0.2532170871981549,"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."}}