{"id":"W2809115655","doi":"10.1029/2018wr022908","title":"Hydroclimatological Drivers of Extreme Floods on Lake Ontario","year":2018,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centrum fÖr Personcentrerad Vård; U.S. Geological Survey","keywords":"Flood myth; Spring (device); Environmental science; Precipitation; Climatology; North Atlantic oscillation; Hydrometeorology; Hydrology (agriculture); Drawdown (hydrology); Drainage basin; Structural basin; Period (music); Subtropics; Atlantic multidecadal oscillation; Water level; Subtropical ridge; Geology; Geography; Meteorology; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008604706,0.0001144651,0.0001478694,0.000115428,0.0002440778,0.00004298459,0.0005289299,0.00006794588,0.01868031],"category_scores_gemma":[0.00001360146,0.00007066043,0.00005574129,0.0001841998,0.0008142494,0.00008511169,0.0008774484,0.0002666876,0.003528814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001404657,"about_ca_system_score_gemma":0.000005343937,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006367084,"about_ca_topic_score_gemma":0.08944234,"domain_scores_codex":[0.9976368,0.0001714755,0.0001844952,0.0003768815,0.001036165,0.0005942069],"domain_scores_gemma":[0.9994269,0.00004024113,0.00002408467,0.0003786734,0.00001841527,0.0001116876],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005263533,0.0009543016,0.890224,0.00004033412,0.00009317633,0.0001281932,0.02692344,0.0003893654,0.02838957,0.000501574,0.04376849,0.008061211],"study_design_scores_gemma":[0.0004807246,0.001039367,0.07961707,0.00001984509,0.000007631656,0.000001797256,0.0002903,0.0003277251,0.02697896,0.0006775292,0.890398,0.0001610519],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8085999,0.00000206925,0.00001365587,0.0003123791,0.00004462037,0.0001973961,0.000001197499,0.0000217438,0.190807],"genre_scores_gemma":[0.9776968,0.0000072223,0.0003937212,0.00005870414,0.00004989737,0.00001723728,0.000006397383,0.00001050825,0.02175951],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8466295,"threshold_uncertainty_score":0.997247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07318600993046853,"score_gpt":0.3154691598938322,"score_spread":0.2422831499633637,"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."}}