{"id":"W2022485051","doi":"10.1016/j.jenvman.2006.08.004","title":"Detection and visualization of storm hydrograph changes under urbanization: An impulse response approach","year":2006,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"Vancouver Aquarium","funders":"","keywords":"Hydrograph; Watershed; Storm; Computer science; Environmental science; Surface runoff; Hydrology (agriculture); Meteorology; Engineering; Geography; Machine learning","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":[0.0002727253,0.0002842143,0.0003117461,0.0009587992,0.0001529001,0.0005126328,0.000204636,0.0004968186,0.002039612],"category_scores_gemma":[0.0008943156,0.0001906431,0.0002724693,0.0005157165,0.000220916,0.0002808264,0.0003974964,0.0003703165,0.0001671004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001568676,"about_ca_system_score_gemma":0.0002391176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001386135,"about_ca_topic_score_gemma":0.001476124,"domain_scores_codex":[0.9999059,0.00002658137,0.000003399451,0.00001341665,0.00002579836,0.00002483874],"domain_scores_gemma":[0.9995391,0.00028847,0.00003894787,0.00002052955,0.00007312825,0.00003971597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002000991,0.000475678,0.02380219,0.0003379086,0.0002368425,0.001387922,0.001118766,0.2180613,0.28625,0.005071431,0.003956084,0.4573009],"study_design_scores_gemma":[0.00004755232,0.0001882258,0.02634847,0.0000177747,0.00005218977,0.0003970258,0.0003576958,0.9468552,0.02265844,0.002051271,0.0009806587,0.00004552788],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6791081,0.0001628154,0.3131179,0.0004825133,0.00004129913,0.00006862624,0.0003340545,0.002361271,0.004323438],"genre_scores_gemma":[0.9635617,0.0001305148,0.03523273,0.00003677668,0.00002033346,0.00002547203,0.00008858823,0.00006754218,0.0008363627],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002039612,"threshold_uncertainty_score":0.006823182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005864851549053661,"score_gpt":0.2011117519167908,"score_spread":0.1952469003677371,"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."}}