{"id":"W4415366627","doi":"10.1088/2634-4505/ae152f","title":"Conveying intermittent water supply schedules digitally: production burdens and consumption possibilities in Coimbatore, India","year":2025,"lang":"en","type":"article","venue":"Environmental Research Infrastructure and Sustainability","topic":"Water resources management and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Schedule; Production (economics); Water supply; Production schedule; Consumption (sociology); Transparency (behavior); Bureaucracy; Corporate governance","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005028091,0.0001509431,0.000146021,0.0002883994,0.0001351289,0.0001525723,0.00008437179,0.00008837046,0.0000483524],"category_scores_gemma":[0.00008201717,0.0001239873,0.00001880503,0.00009020516,0.0005035753,0.0003252485,0.000259041,0.0003253646,0.000001749406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004880799,"about_ca_system_score_gemma":0.00001197477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001633627,"about_ca_topic_score_gemma":0.000009637592,"domain_scores_codex":[0.9987636,0.000106177,0.000223765,0.0003296639,0.0001988741,0.000377925],"domain_scores_gemma":[0.9996849,0.00004441668,0.00001082158,0.0001779582,0.00001938262,0.00006248982],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007239525,0.00003379866,0.9671141,0.0007529137,0.00003028356,0.000009116128,0.003111016,0.004475443,0.0007905848,0.0002494519,0.00008034799,0.02328058],"study_design_scores_gemma":[0.0003945434,0.00004296579,0.9672041,0.00004477072,0.000006923241,0.000002287075,0.005951047,0.00385457,0.004388445,0.01696863,0.0009859614,0.0001557946],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982056,0.0003853922,0.0001869932,0.0001807937,0.00006626771,0.0006684864,0.000006241107,0.00004369205,0.0002565551],"genre_scores_gemma":[0.9989433,0.0003097791,0.00007542216,0.00001198867,0.00002176534,0.0000486176,0.00004818984,0.00001180875,0.0005291144],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02312479,"threshold_uncertainty_score":0.5056056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006286171629391307,"score_gpt":0.2448993348431739,"score_spread":0.2386131632137826,"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."}}