{"id":"W2513011376","doi":"10.1016/j.socscimed.2016.08.049","title":"Reduced burden of childhood diarrheal diseases through increased access to water and sanitation in India: A modeling analysis","year":2016,"lang":"en","type":"article","venue":"Social Science & Medicine","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":84,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Grand Challenges Canada","keywords":"Sanitation; Environmental health; Medicine; Improved sanitation; Diarrheal disease; Child mortality; Baseline (sea); Diarrhea; Population; Disease burden; Water supply; Socioeconomics; Economics; Environmental science; Environmental engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004023873,0.00009748233,0.0002851053,0.00047167,0.0001992523,0.00005061549,0.0002579828,0.00003883241,0.00003403575],"category_scores_gemma":[0.000286535,0.00005671867,0.00003871765,0.001468683,0.0003847076,0.0008651859,0.00006702892,0.00005366583,7.204668e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009115235,"about_ca_system_score_gemma":0.00002685724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00174047,"about_ca_topic_score_gemma":0.00005129894,"domain_scores_codex":[0.9986129,0.00006904947,0.0002867243,0.0003093486,0.0004428728,0.0002790372],"domain_scores_gemma":[0.9995409,0.00005791956,0.00005719363,0.0001025437,0.0001120479,0.0001293886],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009154898,0.0004501202,0.5077,0.0001067833,0.0001175562,0.00001096856,0.2828964,0.0001794923,0.1827376,0.000558842,0.0003140639,0.02401261],"study_design_scores_gemma":[0.003196971,0.0001616255,0.9659864,0.0003204454,0.0003169319,0.00000119493,0.001412444,0.0006266053,0.01870348,0.009003393,0.00002690741,0.0002435592],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821736,0.00004464032,0.0004596668,0.01671987,0.0001263385,0.0002456228,0.00001372014,0.00002115934,0.0001954195],"genre_scores_gemma":[0.9990414,0.00001241746,0.00001614317,0.0005543234,0.000340529,0.00001292139,0.00001441841,0.000006048609,0.0000018345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4582864,"threshold_uncertainty_score":0.2631082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02005100080786319,"score_gpt":0.3324643765380936,"score_spread":0.3124133757302304,"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."}}