{"id":"W1989951002","doi":"10.1016/j.scitotenv.2014.11.096","title":"Local environmental conditions determine the footprint of municipal effluent in coastal waters: A case study in the Strait of Georgia, British Columbia","year":2014,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"British Columbia Institute of Technology; Remotely Operated Platform for Ocean Sciences; Fisheries and Oceans Canada","funders":"Fisheries and Oceans Canada","keywords":"Effluent; Environmental science; Wastewater; Eutrophication; Sewage treatment; Total organic carbon; Outfall; Dredging; Pollutant; Environmental protection; Environmental engineering; Oceanography; Environmental chemistry; Nutrient; 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":[0.0002446922,0.0003407654,0.0002720285,0.001085912,0.002061328,0.001405404,0.0007296003,0.0004983461,0.001009138],"category_scores_gemma":[0.0008920069,0.0002229053,0.0002626126,0.003367131,0.0008267991,0.0002883375,0.0009910106,0.0004344462,0.0001478982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0142656,"about_ca_system_score_gemma":0.007233181,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9666113,"about_ca_topic_score_gemma":0.9914484,"domain_scores_codex":[0.9996951,0.00005692663,0.00001607355,0.00004751506,0.00009125236,0.00009310755],"domain_scores_gemma":[0.9993475,0.0001032648,0.00007112175,0.00003139485,0.0003263314,0.0001203938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001064582,0.0001769608,0.959624,0.0001240813,0.00008557444,0.005524021,0.004561742,0.005296234,0.00380943,0.0004690454,0.001366707,0.0188557],"study_design_scores_gemma":[0.000007452895,0.00005722041,0.9728928,0.0000381837,0.00003565761,0.0003444556,0.02101341,0.003147524,0.0004238127,0.00009873026,0.001916705,0.00002403985],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971293,0.00006297157,0.00008744095,0.00008605082,0.000001248311,0.00002784918,0.0003682943,0.000007958852,0.002228829],"genre_scores_gemma":[0.9974378,0.0001620765,0.0003977643,0.00007431693,0.000001036046,0.00001745725,0.0003173825,0.000006920823,0.001585185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03338867,"threshold_uncertainty_score":0.1035047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01351862140211759,"score_gpt":0.2359127580466308,"score_spread":0.2223941366445132,"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."}}