{"id":"W2182283319","doi":"10.1080/09603123.2015.1089532","title":"The impact of rainfall and seasonal variability on the removal of bacteria by a point-of-use drinking water treatment intervention in Chennai, India","year":2015,"lang":"en","type":"article","venue":"International Journal of Environmental Health Research","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of Guelph","funders":"International Development Research Centre","keywords":"Environmental science; Water quality; Seasonality; Toxicology; Indicator bacteria; Wet season; Water treatment; Monsoon; Contamination; Dry season; Coliform bacteria; Fecal coliform; Environmental engineering; Veterinary medicine; Hydrology (agriculture); Biology; Bacteria; Geography; Ecology; Medicine; Meteorology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003151619,0.0002348963,0.0002110569,0.0003232238,0.0003601067,0.0004845862,0.0004792682,0.0002365829,0.00054082],"category_scores_gemma":[0.0008384755,0.0001649806,0.0002717939,0.0005166291,0.0004393286,0.000196181,0.0003542273,0.0003547191,0.00008899263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009572168,"about_ca_system_score_gemma":0.0008411547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04527744,"about_ca_topic_score_gemma":0.09322803,"domain_scores_codex":[0.9995307,0.0001692834,0.00002983744,0.00008608204,0.00008108761,0.000102992],"domain_scores_gemma":[0.9991142,0.0003539649,0.0002040345,0.00006827402,0.0001166631,0.0001428239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003167529,0.001491001,0.8771673,0.0002648466,0.0003265826,0.001423964,0.004506064,0.002185683,0.06824536,0.0001691129,0.000572944,0.04047957],"study_design_scores_gemma":[0.00001118945,0.001136935,0.9941292,0.000004257773,0.00004238208,0.000128444,0.001090922,0.00038183,0.002859146,0.00001738727,0.0001871485,0.00001124415],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996879,0.00001949108,0.00004911107,0.00001441672,0.000001997312,0.000006820773,0.00003805171,0.00000354036,0.000178731],"genre_scores_gemma":[0.9996324,0.00003410529,0.00009967763,0.00001288311,0.000002012059,0.000007599939,0.00005445625,0.000001642098,0.0001552301],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04527744,"threshold_uncertainty_score":0.09002781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08225153661982997,"score_gpt":0.4132816046141515,"score_spread":0.3310300679943216,"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."}}