{"id":"W4324057287","doi":"10.2166/ws.2023.072","title":"Water scarcity and excess: water insecurity in cities of Nepal","year":2023,"lang":"en","type":"article","venue":"Water Science & Technology Water Supply","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Water scarcity; Water security; Scarcity; Water quality; Business; Context (archaeology); Water resources; Environmental planning; Natural resource economics; Water supply; Corporate governance; Environmental resource management; Geography; Environmental science; Economics; Environmental engineering; Ecology","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001191409,0.0003702015,0.000537275,0.003244716,0.0004630082,0.0002140701,0.001193044,0.0003375746,0.0001497331],"category_scores_gemma":[0.00001871241,0.0001890257,0.00008248989,0.000936245,0.003135219,0.001129031,0.001489009,0.0004763325,0.0002690001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008959431,"about_ca_system_score_gemma":0.00001291262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003747248,"about_ca_topic_score_gemma":0.0001390733,"domain_scores_codex":[0.9959997,0.00008269428,0.0006650825,0.0009662615,0.0005226014,0.001763677],"domain_scores_gemma":[0.9989579,0.00001623437,0.00003376509,0.0006885598,0.0001696859,0.0001338227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001548208,0.0001282515,0.2442478,0.0001482136,0.000008981688,0.00007534884,0.01835756,0.000008130264,0.7356334,0.0001179523,0.0001815649,0.000937907],"study_design_scores_gemma":[0.001206529,0.000178626,0.01190231,0.00006454969,0.00001344141,0.00006938292,0.0004412835,0.0001597061,0.9576469,0.02467069,0.00327612,0.000370441],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9713746,0.00002903532,0.00001149635,0.02666587,0.0007661974,0.000434153,0.00001813074,0.0005279072,0.0001726127],"genre_scores_gemma":[0.9990654,0.0000208537,0.000146969,0.0003306957,0.00006312694,0.00007555506,0.00007938341,0.000033576,0.0001844394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2323455,"threshold_uncertainty_score":0.9995777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0119157073740638,"score_gpt":0.2510206044166428,"score_spread":0.239104897042579,"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."}}