{"id":"W4417088487","doi":"10.1093/inthealth/ihaf138","title":"Bayesian modeling of <i>Escherichia coli</i> contamination in household drinking water in Bangladesh: evidence from the Multiple Indicator Cluster Survey 2019","year":2025,"lang":"en","type":"article","venue":"International Health","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Manitoba Health; University of Calgary","funders":"Canada Research Chairs; UNICEF","keywords":"Cluster (spacecraft); Fecal coliform; Contamination; Psychological intervention; Population; Feces; Bayesian probability; Waterborne diseases","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":[0.001181194,0.0001169127,0.0002125694,0.0002689105,0.0000631087,0.00005834668,0.000403089,0.00007727434,0.00001564481],"category_scores_gemma":[0.000154396,0.00009032334,0.00004286438,0.0002121696,0.00003186351,0.0002881092,0.00008913741,0.0002882151,0.000003978232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003747919,"about_ca_system_score_gemma":0.00005990265,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03194936,"about_ca_topic_score_gemma":0.03515242,"domain_scores_codex":[0.9981617,0.0004171828,0.0006356258,0.0002730453,0.0002891482,0.0002233256],"domain_scores_gemma":[0.998906,0.000697036,0.0001240558,0.0001759578,0.00006139315,0.00003556522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005184961,0.0001571445,0.9912041,0.0000315464,0.00001214841,0.000001010898,0.002211017,0.00364732,0.0003962759,0.00002597811,0.0008341719,0.0009607573],"study_design_scores_gemma":[0.001904414,0.00002616228,0.7949952,0.001151892,0.000003249032,4.110731e-7,0.0000927888,0.1974469,0.003541881,0.0005096992,0.0002265733,0.0001008207],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9697803,0.0002756105,0.005619815,0.02276949,0.0009307354,0.0004663091,0.00008069057,0.00002284246,0.00005422581],"genre_scores_gemma":[0.9943804,0.00006654986,0.0002168905,0.00495882,0.00008066861,0.00002279646,0.0002359301,0.00001375876,0.00002419988],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1962089,"threshold_uncertainty_score":0.9824535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03785248095541708,"score_gpt":0.3133738295213473,"score_spread":0.2755213485659302,"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."}}