{"id":"W4399847647","doi":"10.1016/j.ejrh.2026.103543","title":"Adaptation of Dual Drainage to Control Flooding and Enhance Combined Sewer Systems in Highly Urbanized Areas","year":2024,"lang":"en","type":"preprint","venue":"Journal of Hydrology Regional Studies","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Flooding (psychology); Drainage; Adaptation (eye); Dual (grammatical number); Water resource management; Environmental science; Drainage system (geomorphology); Geography; Environmental planning; Environmental resource management; Ecology; Biology; Psychology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0001798328,0.0003273851,0.000339482,0.0002799536,0.0002184819,0.0006618128,0.0005855703,0.0004164313,0.000819194],"category_scores_gemma":[0.0004289655,0.0002226126,0.0003286228,0.0001991584,0.0004122588,0.0003743429,0.0006499351,0.0002388897,0.00006968107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006578966,"about_ca_system_score_gemma":0.001084263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02081303,"about_ca_topic_score_gemma":0.02598565,"domain_scores_codex":[0.9998624,0.00002955519,0.000004695428,0.00003213404,0.00002870774,0.00004247838],"domain_scores_gemma":[0.9998844,0.0000272155,0.0000251715,0.00001365362,0.00002714655,0.00002247191],"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":[0.00006928678,0.0001366115,0.004751534,0.00002785708,0.00001901373,0.0000947994,0.0000410464,0.9670615,0.01399415,0.0008909586,0.0001448478,0.01276827],"study_design_scores_gemma":[0.00001823923,0.00007445932,0.001482505,0.000001831646,0.000008927048,0.00001098087,0.0000223168,0.9957681,0.002027127,0.0002054206,0.0003746397,0.000005481599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8439019,0.00008161166,0.1507176,0.0001246326,0.00001781911,0.0001238241,0.00009503836,0.0003424193,0.004595186],"genre_scores_gemma":[0.9908064,0.00002314154,0.008286829,0.000005393239,0.00000165076,0.00002553751,0.00001653187,0.000007426923,0.0008270518],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02081303,"threshold_uncertainty_score":0.04138374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02872300471588779,"score_gpt":0.2684349150206719,"score_spread":0.2397119103047841,"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."}}