{"id":"W2906354380","doi":"10.1371/journal.pone.0209470","title":"Opportunities for natural infrastructure to improve urban water security in Latin America","year":2018,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Snap; Science for Nature and People Partnership; Nature Conservancy; Wildlife Conservation Society; Inter-American Development Bank; Gordon and Betty Moore Foundation","keywords":"Impervious surface; Watershed; Stormwater; Flood myth; Water quality; Riparian zone; Environmental planning; Green infrastructure; Flood mitigation; Watershed management; Urbanization; Wetland; Ecosystem services; Business; Geospatial analysis; Environmental resource management; Water resource management; Environmental protection; Environmental science; Geography; Surface runoff; Ecosystem; Habitat; Ecology","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":[0.0004057206,0.0002427206,0.0001190038,0.001483042,0.0003846126,0.001287003,0.0002356902,0.0001911369,0.002219043],"category_scores_gemma":[0.001549109,0.0001011006,0.0003012981,0.002644736,0.0005202175,0.0008465564,0.001140875,0.0001940769,0.00008742676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001271316,"about_ca_system_score_gemma":0.001121597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0429209,"about_ca_topic_score_gemma":0.07388791,"domain_scores_codex":[0.9997559,0.00008328978,0.0000126722,0.00003773663,0.00004199447,0.00006848062],"domain_scores_gemma":[0.9995951,0.00009134755,0.0001524889,0.0000383711,0.00008545668,0.00003724087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005249402,0.00009021352,0.8632208,0.000208919,0.0001591059,0.0003574016,0.002550792,0.009393265,0.001997741,0.01522064,0.003713225,0.1030355],"study_design_scores_gemma":[0.00002161331,0.0000753291,0.9219646,0.000245483,0.0001172294,0.0001953791,0.01447993,0.008872666,0.001101393,0.008202957,0.04469724,0.00002634225],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9465221,0.001392908,0.004764225,0.002767317,0.00001516818,0.00006847842,0.001742943,0.0001026413,0.04262421],"genre_scores_gemma":[0.9953825,0.0006907511,0.002236049,0.0001131728,0.000007205143,0.00005209293,0.0005822096,0.00001240199,0.0009235217],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0429209,"threshold_uncertainty_score":0.08534211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03137479779088177,"score_gpt":0.2119449498658019,"score_spread":0.1805701520749201,"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."}}