{"id":"W2997013792","doi":"","title":"Mercury Mobilization in Urban Stormwater Runoff","year":2007,"lang":"en","type":"article","venue":"AGUFM","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; General Electric (Canada)","funders":"","keywords":"Surface runoff; First flush; Environmental science; Stormwater; Hydrology (agriculture); Hydrograph; Sink (geography); Particulates; Urban runoff; Pollutant; Mercury (programming language); Drainage basin; Environmental engineering; Geography; Geology; Chemistry","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003552416,0.00009044301,0.00007029512,0.00007433476,0.0000625426,0.00001339947,0.000159824,0.00004405242,0.001576537],"category_scores_gemma":[0.00001008859,0.00008565535,0.00002594035,0.0002995032,0.00007568584,0.0002886285,0.0001337232,0.00007300237,0.001759682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002747501,"about_ca_system_score_gemma":0.00000213254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00106098,"about_ca_topic_score_gemma":0.00212369,"domain_scores_codex":[0.9990726,0.00002007183,0.0001791668,0.000223114,0.0001998349,0.000305289],"domain_scores_gemma":[0.9996671,0.00001543035,0.0000319133,0.000226051,0.000002763273,0.00005670611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001553811,0.0001782097,0.96007,0.000005803562,0.000008072521,0.00003083786,0.001831693,0.003498434,0.009675565,0.000719178,0.02045552,0.003511129],"study_design_scores_gemma":[0.0003270023,0.00003522671,0.8051708,0.000006945022,0.000009763394,0.000002001303,0.0001398141,0.001390609,0.001681181,0.0003659174,0.1906459,0.0002247457],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9511581,0.0000303894,0.00353993,0.0001604406,0.0001906222,0.000217261,0.000001088165,0.00007139651,0.04463075],"genre_scores_gemma":[0.9939823,0.000004049053,0.000542236,0.0002437539,0.00003448487,0.0000103544,0.00001040752,0.00001194923,0.005160425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1701904,"threshold_uncertainty_score":0.9993362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008206969495867135,"score_gpt":0.2160218217123378,"score_spread":0.2078148522164707,"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."}}