{"id":"W2799820518","doi":"10.1002/2018ef000823","title":"Managing the Cascading Risks of Droughts: Institutional Adaptation in Transboundary River Basins","year":2018,"lang":"en","type":"article","venue":"Earth s Future","topic":"Water resources management and optimization","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Horizon 2020 Framework Programme; European Commission","keywords":"Interdependence; Environmental resource management; Upstream (networking); Context (archaeology); Corporate governance; Environmental planning; Downstream (manufacturing); Business; Adaptation (eye); Human systems engineering; Climate change; Geography; Environmental science; Computer science; Political science; 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":[],"consensus_categories":[],"category_scores_codex":[0.00008793269,0.00007064886,0.00006328592,0.00009075247,0.00008954574,0.00002348799,0.00008320697,0.00003788496,0.00005061342],"category_scores_gemma":[0.000002008605,0.0000549853,0.00002554772,0.0002170269,0.00007271118,0.0001859742,0.000009821551,0.0000929055,0.00001270676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001420345,"about_ca_system_score_gemma":0.000005367783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004037892,"about_ca_topic_score_gemma":0.0005117167,"domain_scores_codex":[0.9995722,0.00001751369,0.0001183945,0.00007652451,0.0001095586,0.0001057615],"domain_scores_gemma":[0.9998564,0.000007323553,0.00001882065,0.00008753158,0.00001704685,0.00001292743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002542102,0.00001469441,0.002102325,0.00008341596,0.00004404478,0.000007669183,0.02159873,0.931148,0.0001331883,0.003069641,0.0004185682,0.04135432],"study_design_scores_gemma":[0.0005546302,0.00003023766,0.06790594,0.00008304678,0.00002333676,0.000003014119,0.0008682692,0.7566156,0.0008614776,0.0005895902,0.172294,0.0001708409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8531234,0.000545025,0.1246485,0.0005141855,0.0009834521,0.0002946141,0.0000123652,0.0001308519,0.01974759],"genre_scores_gemma":[0.9974841,0.00007432476,0.001817503,0.00004018593,0.0004432366,0.000003548285,0.00001663795,0.000009257588,0.0001112443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1745324,"threshold_uncertainty_score":0.2242235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02091482498565804,"score_gpt":0.2204167852063001,"score_spread":0.1995019602206421,"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."}}