{"id":"W4382398044","doi":"10.1016/j.jclepro.2023.137931","title":"Developing sustainable strategies by LID optimization in response to annual climate change impacts","year":2023,"lang":"en","type":"article","venue":"Journal of Cleaner Production","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Environmental science; Climate change; Surface runoff; Storm Water Management Model; Drainage; Precipitation; Flood myth; Drainage basin; Low-impact development; Meteorology; Storm; Climate model; Hydrology (agriculture); Climatology; Stormwater; Engineering; Geography; Stormwater management; Geology","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":[0.001053941,0.0006049659,0.0005035772,0.0007015627,0.0004126671,0.001892547,0.0006933923,0.0009317544,0.00549959],"category_scores_gemma":[0.001870382,0.0003405233,0.0005031634,0.0004775526,0.0004117609,0.001523191,0.001410778,0.0007168367,0.0005581873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009311018,"about_ca_system_score_gemma":0.00207738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003132245,"about_ca_topic_score_gemma":0.006544577,"domain_scores_codex":[0.9996411,0.0001074286,0.00001459949,0.00005000424,0.0000694334,0.0001173964],"domain_scores_gemma":[0.9995752,0.0001634118,0.00006522963,0.00004374664,0.0001085547,0.00004396433],"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":[0.00007257798,0.0001151609,0.002472996,0.00008116015,0.00005314416,0.0000695793,0.00005138525,0.9244788,0.005773913,0.0159938,0.001736169,0.04910135],"study_design_scores_gemma":[0.00001765155,0.0001046851,0.0005647877,0.00001633453,0.00002469724,0.00001421601,0.0002072743,0.982389,0.002084917,0.01124717,0.003320656,0.000008643351],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.234317,0.0005715276,0.6948365,0.001630342,0.0002080988,0.0002725396,0.0004491254,0.001107929,0.06660701],"genre_scores_gemma":[0.9299396,0.0002205252,0.06427718,0.0001393052,0.0000174677,0.0001241617,0.0001377466,0.00008653163,0.005057526],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00549959,"threshold_uncertainty_score":0.01839799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02075318844962083,"score_gpt":0.2692094754410999,"score_spread":0.248456286991479,"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."}}