{"id":"W4389950029","doi":"10.1007/s11269-023-03698-4","title":"A Set Pair Analysis Method for Assessing and Forecasting Water Conflict Risk in Transboundary River Basins","year":2023,"lang":"en","type":"article","venue":"Water Resources Management","topic":"Water resources management and optimization","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"National Natural Science Foundation of China","keywords":"Hydrogeology; Water resource management; Environmental science; Set (abstract data type); Hydrology (agriculture); Geology; Operations research; Computer science; Engineering; Geotechnical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00244918,0.001062147,0.001692345,0.004610367,0.00122811,0.001675032,0.001515297,0.001370312,0.003638601],"category_scores_gemma":[0.006682797,0.000696372,0.001920906,0.00219912,0.0006352367,0.002104384,0.001536655,0.001434219,0.0004119249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001086528,"about_ca_system_score_gemma":0.001204313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007340321,"about_ca_topic_score_gemma":0.005475108,"domain_scores_codex":[0.9985394,0.0006471741,0.00008383113,0.0002294106,0.0004011211,0.00009901809],"domain_scores_gemma":[0.9956542,0.002964768,0.0002595547,0.0002556082,0.0007047399,0.0001610232],"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":[0.0004611142,0.0003371564,0.01228517,0.0001130501,0.0004677024,0.0001813318,0.0002019256,0.7253056,0.004251655,0.01194443,0.002848154,0.2416027],"study_design_scores_gemma":[0.000008357722,0.00005848014,0.0005631932,0.000005637477,0.00002627787,0.00002299686,0.00001682054,0.9962904,0.0005389563,0.0022272,0.0002308166,0.00001069832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06936318,0.0002128019,0.9273146,0.0001114136,0.00007423136,0.000140803,0.0003080236,0.0004715362,0.002003504],"genre_scores_gemma":[0.6012709,0.0001719599,0.3954432,0.00008134037,0.00006509873,0.0003227541,0.0005982328,0.00009884335,0.001947678],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007340321,"threshold_uncertainty_score":0.01459515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0269639952558059,"score_gpt":0.249968509327777,"score_spread":0.2230045140719711,"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."}}