{"id":"W2032600085","doi":"10.1007/s11270-010-0703-7","title":"Mercury Cycling in an Urbanized Watershed: The Influence of Wind Distribution and Regional Subwatershed Geometry in Central Indiana, USA","year":2010,"lang":"en","type":"article","venue":"Water Air & Soil Pollution","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Indiana University-Purdue University Indianapolis","keywords":"Watershed; Impervious surface; Environmental science; Hydrology (agriculture); Sedimentary depositional environment; Mercury (programming language); Tributary; Deposition (geology); Prevailing winds; Soil water; Geology; Structural basin; Geography; Geomorphology; Soil science; Ecology; Oceanography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001619992,0.0001610628,0.0002154928,0.0004359226,0.0006048241,0.0006971944,0.0003291191,0.0002124178,0.0005205369],"category_scores_gemma":[0.0002225088,0.0002208743,0.000171436,0.0009655397,0.0003926992,0.0002612551,0.0003937037,0.0001712829,0.00007677608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001418255,"about_ca_system_score_gemma":0.001176439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3062837,"about_ca_topic_score_gemma":0.5721734,"domain_scores_codex":[0.9998749,0.00003786738,0.00000958306,0.00003183305,0.00001997279,0.00002576127],"domain_scores_gemma":[0.9998208,0.00003998045,0.00004223304,0.00001039359,0.00004415091,0.00004257455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001916646,0.0001678531,0.9934749,0.000009734386,0.00005956186,0.000184414,0.0005661677,0.0007027093,0.002068276,0.00009867686,0.0001459824,0.002329927],"study_design_scores_gemma":[0.000007974572,0.00005177096,0.9956205,0.000004419418,0.00002916204,0.00006846493,0.001875901,0.00166792,0.0004552882,0.00004193007,0.0001722947,0.000004341311],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997197,0.00001091471,0.00002255131,0.00001021786,4.099738e-7,0.000002005794,0.00007441026,0.000001725554,0.0001580154],"genre_scores_gemma":[0.999495,0.00003256187,0.0001007447,0.000009338576,0.000001126749,0.000003276183,0.0001439399,8.896729e-7,0.0002130621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3062837,"threshold_uncertainty_score":0.6090019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009857559629681285,"score_gpt":0.2314470754220346,"score_spread":0.2215895157923533,"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."}}