{"id":"W2999807168","doi":"10.1002/hyp.13697","title":"Water age in stormwater management ponds and stormwater management pond‐treated catchments","year":2020,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Impervious surface; Hydrology (agriculture); Environmental science; Stormwater; Water quality; Baseflow; Drainage basin; Land cover; Watershed; Infiltration (HVAC); Surface water; Land use; Surface runoff; Streamflow; Geology; Environmental engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002267906,0.0004075737,0.0003352391,0.0001181765,0.0001897265,0.0001044666,0.0005111258,0.0001185551,0.001715427],"category_scores_gemma":[0.000008972817,0.0002739655,0.00005157852,0.0004556933,0.0002999849,0.0004727342,0.001451067,0.0002170599,0.001656712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001850952,"about_ca_system_score_gemma":0.00000176309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006806586,"about_ca_topic_score_gemma":0.0000685617,"domain_scores_codex":[0.9971341,0.00007785201,0.0004344003,0.001006613,0.0004891554,0.0008578109],"domain_scores_gemma":[0.9993526,0.00001615844,0.00005924882,0.0003024615,0.000008343157,0.0002611448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001512005,0.003126257,0.890019,0.002810121,0.0008605343,0.01068538,0.01410773,0.00701013,0.01530652,0.001152578,0.04559264,0.007817123],"study_design_scores_gemma":[0.008796661,0.001728096,0.4630711,0.0001569596,0.0006381052,0.0000470429,0.001024468,0.002513495,0.01102298,0.00802298,0.4993473,0.003630772],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9549463,0.00007529943,0.0002716858,0.00295159,0.00005624581,0.0009225847,0.000006018205,0.0002497015,0.04052055],"genre_scores_gemma":[0.9912526,0.0001226719,0.0005912448,0.002901371,0.00003066433,0.0002303926,0.0000603413,0.00003172432,0.00477897],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4537547,"threshold_uncertainty_score":0.9999713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01931092953049691,"score_gpt":0.210560948785753,"score_spread":0.1912500192552561,"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."}}