{"id":"W4392901840","doi":"10.53328/inr24gar011","title":"Unmasking the Unseen: The Gendered Impacts of Water Quality, Sanitation and Hygiene","year":2024,"lang":"en","type":"report","venue":"","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"United Nations University Institute for Water, Environment, and Health; Global Affairs Canada","funders":"Global Affairs Canada; Government of Canada","keywords":"Sanitation; Hygiene; Environmental health; Water quality; Socioeconomic status; Public health; Data collection; Environmental planning; Socioeconomics; Business; Geography; Medicine; Nursing; Sociology; Population","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":[0.006542166,0.0004398968,0.0004711688,0.0005457184,0.002307003,0.00305424,0.0004911227,0.0006932701,0.003975514],"category_scores_gemma":[0.005440771,0.0002191253,0.000341604,0.0005029943,0.006981142,0.003232603,0.004323442,0.001318522,0.000238356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001429613,"about_ca_system_score_gemma":0.002581809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006483135,"about_ca_topic_score_gemma":0.0125294,"domain_scores_codex":[0.9959447,0.002586961,0.00009356568,0.0003654286,0.0006122424,0.0003971272],"domain_scores_gemma":[0.9963497,0.002403483,0.0004572263,0.0002480788,0.0003426974,0.0001987649],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005693521,0.0001998273,0.3270076,0.001527554,0.0001388821,0.003210396,0.2222733,0.0009018736,0.01318274,0.09751379,0.003871724,0.329603],"study_design_scores_gemma":[0.00001718843,0.001157547,0.3899479,0.002464319,0.0001651017,0.001930995,0.4497079,0.001026568,0.007102005,0.05253235,0.0938161,0.0001320281],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.9131948,0.0105816,0.008185817,0.01944202,0.0005859679,0.0001143922,0.0003015099,0.00002300787,0.04757078],"genre_scores_gemma":[0.9939353,0.001851708,0.0013755,0.001135503,0.00007094519,0.00003133652,0.00001676056,0.000006494828,0.001576467],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.006542166,"threshold_uncertainty_score":0.03459865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07148951908552385,"score_gpt":0.3677723611850608,"score_spread":0.2962828420995369,"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."}}