{"id":"W4311947032","doi":"10.3389/fenvs.2022.958101","title":"Replenishing the Indus Delta through multi-sector transformation","year":2022,"lang":"en","type":"article","venue":"Frontiers in Environmental Science","topic":"Water-Energy-Food Nexus Studies","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Global Environment Fund; Natural Sciences and Engineering Research Council of Canada; Global Environment Facility","keywords":"Indus; Upstream (networking); Delta; Water resource management; Irrigation; Environmental science; Structural basin; Ecosystem; Ecosystem services; Business; Vulnerability (computing); Environmental resource management; Drainage basin; Water resources; Hydrology (agriculture); Natural resource economics; Geography; Ecology; Geology; Economics; Engineering; Geomorphology","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":[0.0007038574,0.0003331482,0.0003408208,0.0003659677,0.0006553571,0.001922935,0.0007915772,0.0006311499,0.004400529],"category_scores_gemma":[0.001011874,0.0001549482,0.0005912543,0.000535793,0.000873741,0.001803779,0.002618198,0.0006405553,0.0001893821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002814874,"about_ca_system_score_gemma":0.003494698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01309258,"about_ca_topic_score_gemma":0.0185686,"domain_scores_codex":[0.9996208,0.0001825858,0.00001050773,0.00004608349,0.00004961206,0.00009046732],"domain_scores_gemma":[0.9996024,0.00009869601,0.00008088188,0.0000610553,0.00005929285,0.00009767967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.000259981,0.0003447603,0.02512209,0.000118133,0.0001053733,0.0006228904,0.0003955272,0.8635464,0.001971794,0.0763664,0.001704808,0.02944175],"study_design_scores_gemma":[0.0001622589,0.0004634583,0.01641928,0.00006077586,0.00008312591,0.0001635265,0.002761547,0.894716,0.001357133,0.0682679,0.01550275,0.00004240646],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9208261,0.0001991883,0.03164721,0.001557423,0.00004409845,0.0001844648,0.0002679977,0.0001300937,0.0451434],"genre_scores_gemma":[0.9962078,0.00007774694,0.002444431,0.00004497116,0.000002757635,0.00004063283,0.0000350475,0.000005229835,0.001141199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01309258,"threshold_uncertainty_score":0.02603275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01657749033653867,"score_gpt":0.2066410453443673,"score_spread":0.1900635550078286,"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."}}