{"id":"W4210933056","doi":"10.5194/essd-14-559-2022","title":"Distribution and characteristics of wastewater treatment plants within the global river network","year":2022,"lang":"en","type":"article","venue":"Earth system science data","topic":"Water Treatment and Disinfection","field":"Environmental Science","cited_by":216,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Universiteit Utrecht; McGill University","keywords":"Environmental science; Effluent; Sewage treatment; Outfall; Wastewater; Pollutant; Geospatial analysis; Population; Streamflow; Water resource management; Hydrology (agriculture); Environmental engineering; Drainage basin; Geography; Ecology; Remote sensing; Cartography","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":[],"consensus_categories":[],"category_scores_codex":[0.0005740349,0.00008089255,0.00009420031,0.000006839257,0.0006484506,0.0000498286,0.0003822164,0.00001021201,0.00006380232],"category_scores_gemma":[0.00000637992,0.0000479927,0.00001166415,0.0002491742,0.0003688656,0.0002995027,0.0007755254,0.00002708687,0.00003728273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002010636,"about_ca_system_score_gemma":0.00002036231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008055005,"about_ca_topic_score_gemma":0.00007003676,"domain_scores_codex":[0.9989322,0.00007220883,0.0001529086,0.0002995795,0.0003623294,0.0001807619],"domain_scores_gemma":[0.9993144,0.00001289333,0.0001102878,0.0005065817,0.00000331362,0.0000525678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004955676,0.00009782721,0.9926907,0.000008082501,0.00001460031,0.00001215893,0.0006106379,0.001349919,0.0006109329,0.0005288961,0.0006538591,0.003372761],"study_design_scores_gemma":[0.0003451374,0.0002416924,0.9836931,0.00001460151,0.00003309975,0.0001068203,0.0004954456,0.00948884,0.0006287644,0.00005212472,0.004782731,0.0001176629],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971188,0.00001534483,0.00006129252,0.00004561229,0.0003240761,0.0002110226,0.001893403,0.00001635336,0.0003141123],"genre_scores_gemma":[0.9992791,0.000002515979,0.00006849269,0.000007854102,0.00002845224,0.00001025382,0.000541785,0.000001833478,0.00005969678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008997688,"threshold_uncertainty_score":0.4987423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01805486727674711,"score_gpt":0.2214275658210118,"score_spread":0.2033726985442647,"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."}}