{"id":"W2170015719","doi":"10.1002/hyp.1064","title":"System dynamics model for predicting floods from snowmelt in North American prairie watersheds","year":2002,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":137,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Resources Canada; U.S. Geological Survey","keywords":"Snowmelt; Environmental science; Streamflow; Hydrology (agriculture); Watershed; Flood myth; Interception; Flood forecasting; Drainage basin; Snow; Precipitation; Meteorology; Geology; Geography; Computer science","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":[0.000692977,0.0006440553,0.0005144361,0.0006533969,0.0007943682,0.00107159,0.000606987,0.0009529187,0.003028906],"category_scores_gemma":[0.001878429,0.0004939314,0.000493857,0.0003539143,0.0003467965,0.0007381563,0.0005330721,0.0009468681,0.0002935897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001552084,"about_ca_system_score_gemma":0.001539305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07949034,"about_ca_topic_score_gemma":0.04932539,"domain_scores_codex":[0.9998426,0.00005245696,0.000009409905,0.00003819781,0.00003040934,0.00002692266],"domain_scores_gemma":[0.999436,0.0003731289,0.00005973136,0.00001104684,0.00009014463,0.00003001131],"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":[0.0000293154,0.00003949083,0.004428398,0.00001340447,0.00002352369,0.00003604573,0.00003174966,0.9926595,0.0002050443,0.0005948344,0.0002702616,0.001668487],"study_design_scores_gemma":[0.0000070306,0.000008328097,0.0005703564,0.000001219462,0.000002666785,0.00000160379,0.000007799023,0.9990951,0.00003016492,0.000186455,0.00008775925,0.00000151424],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9306906,0.000179278,0.06026349,0.0005090262,0.00004530799,0.0001609681,0.002021096,0.0007453659,0.00538478],"genre_scores_gemma":[0.9913,0.00006645252,0.006107402,0.00002175181,0.000009004578,0.0001529956,0.0006947239,0.00002383657,0.001623847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07949034,"threshold_uncertainty_score":0.1580553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02030351395010353,"score_gpt":0.2183119363191222,"score_spread":0.1980084223690187,"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."}}