{"id":"W4410202973","doi":"10.1016/j.aei.2025.103429","title":"A novel explainable stacking ensemble model for estimating design floods: A data-driven approach for ungauged regions","year":2025,"lang":"en","type":"article","venue":"Advanced Engineering Informatics","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Stacking; Computer science; Data mining; Artificial intelligence; Physics","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":[0.0009990761,0.000783088,0.000943915,0.0007381288,0.0005086384,0.000855059,0.001737133,0.00108418,0.001398036],"category_scores_gemma":[0.002325201,0.0006453777,0.001145012,0.0009300675,0.0003602652,0.00112107,0.0008979735,0.001311003,0.0003911356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005138634,"about_ca_system_score_gemma":0.001226277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0162063,"about_ca_topic_score_gemma":0.02588858,"domain_scores_codex":[0.9997804,0.00005903481,0.0000123942,0.00007269748,0.00003908965,0.00003645707],"domain_scores_gemma":[0.9993008,0.0003601014,0.00007565479,0.00007548233,0.0001487205,0.00003924298],"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":[0.00002179505,0.00002371765,0.001150013,0.00001076524,0.00004196369,0.00002276015,0.00001630068,0.9766402,0.0005718971,0.001806022,0.0004050111,0.01928955],"study_design_scores_gemma":[8.711208e-7,0.000002176522,0.00007411052,7.217095e-7,0.00000309701,0.000001740984,0.000001015896,0.9992645,0.00004167068,0.0005498586,0.00005846667,0.000001631655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0537919,0.0001814318,0.9439296,0.0001978107,0.00004630549,0.0000254752,0.0005137929,0.0006822973,0.000631384],"genre_scores_gemma":[0.7739193,0.0003475964,0.2192839,0.0001669201,0.0001408499,0.0001989727,0.002282588,0.0002281736,0.003431618],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0162063,"threshold_uncertainty_score":0.03222394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03901509068451805,"score_gpt":0.2595417244425357,"score_spread":0.2205266337580176,"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."}}