{"id":"W4400673815","doi":"10.1139/er-2023-0094","title":"Toward a Canadian national river water quality modeling system: state of science and future prospects","year":2024,"lang":"en","type":"article","venue":"Environmental Reviews","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick; University of Victoria; Environment and Climate Change Canada","funders":"","keywords":"Water quality; Environmental science; State (computer science); Environmental resource management; Environmental planning; Quality (philosophy); Water resource management; Hydrology (agriculture); Environmental protection; Geography; Ecology; Engineering; Biology; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.01570863,0.001774418,0.001380793,0.004529143,0.003938517,0.008454916,0.007558839,0.001566183,0.004539209],"category_scores_gemma":[0.01884288,0.0008841812,0.002259207,0.01067294,0.001709621,0.004619621,0.002898131,0.002940099,0.001351971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03991064,"about_ca_system_score_gemma":0.1296535,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9766516,"about_ca_topic_score_gemma":0.9779412,"domain_scores_codex":[0.9961848,0.0007810836,0.000262103,0.0004097914,0.001996169,0.0003660638],"domain_scores_gemma":[0.9784756,0.002243823,0.0005567321,0.001107141,0.01623998,0.001376712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003860836,0.0003159141,0.06045019,0.00404165,0.0008500107,0.0001930362,0.001781564,0.1639667,0.003569842,0.05954504,0.2321835,0.4727165],"study_design_scores_gemma":[0.0001659774,0.0001354833,0.02561216,0.003275909,0.000681022,0.00005990065,0.001339504,0.3884566,0.002158252,0.014968,0.5627158,0.0004314283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.07073699,0.07524714,0.4498897,0.1133978,0.002167976,0.002914975,0.1311201,0.03446494,0.1200603],"genre_scores_gemma":[0.1453163,0.06340585,0.6971352,0.0062361,0.0003747942,0.001363318,0.07544927,0.001839435,0.008879742],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.03991064,"threshold_uncertainty_score":0.2895734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02351101542694575,"score_gpt":0.2480950948646374,"score_spread":0.2245840794376917,"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."}}