{"id":"W1991905673","doi":"10.1021/es901988y","title":"Pressure Monitoring and Characterization of External Sources of Contamination at the Site of the Payment Drinking Water Epidemiological Studies","year":2009,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Fecal contamination and water quality","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Institut National de la Recherche Scientifique; Natural Sciences and Engineering Research Council of Canada","funders":"Polytechnique Montréal; Natural Sciences and Engineering Research Council of Canada; Texas AgriLife Research","keywords":"Contamination; Environmental science; Water quality; Environmental engineering; Intrusion; Population; Fecal coliform; Environmental health; Geology; Medicine; Ecology; Biology","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.000799367,0.00008811964,0.0001672925,0.00004482961,0.0002094251,0.000004180023,0.0002757078,0.00005695334,0.00006311856],"category_scores_gemma":[0.00004661139,0.00004237499,0.0000312912,0.0001660626,0.00287744,0.0001441381,0.0005942481,0.00008116935,0.000003083519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009733318,"about_ca_system_score_gemma":0.000001668421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001222747,"about_ca_topic_score_gemma":0.000002590276,"domain_scores_codex":[0.9989,0.00008338375,0.0002920291,0.0002222894,0.0003348102,0.0001675041],"domain_scores_gemma":[0.9995115,0.0000367368,0.0002217704,0.0002052312,0.000005260988,0.00001945185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000003946917,0.00002354346,0.3875973,0.000002005349,0.000001828819,1.095504e-7,0.0006994784,0.00004071728,0.6069714,0.00006871413,2.811926e-7,0.004590722],"study_design_scores_gemma":[0.0000571271,0.00005985169,0.5073541,0.00001047651,0.000006647194,0.000002180583,0.0001675391,0.00006302285,0.4919287,0.0002542845,0.00006916219,0.00002698934],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998554,0.0001230537,0.00009259499,0.0009446847,0.00004982372,0.0001903355,0.000003363332,0.000008310395,0.0000338444],"genre_scores_gemma":[0.9996458,0.00008018649,0.00006425688,0.00003957259,0.000005635115,0.000005937726,8.231719e-7,0.000001846783,0.000155969],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1197568,"threshold_uncertainty_score":0.9998361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0157654279505707,"score_gpt":0.2533349646320707,"score_spread":0.2375695366815,"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."}}