{"id":"W2965883164","doi":"10.5194/hess-24-1543-2020","title":"Historical and future changes in global flood magnitude – evidence from a model–observation investigation","year":2020,"lang":"en","type":"article","venue":"Hydrology and earth system sciences","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bundesministerium für Bildung und Forschung; Ministry of Land, Infrastructure, Transport and Tourism; University of Adelaide; Grains Research and Development Corporation; U.S. Geological Survey; European Commission; University of Michigan; ArcticNet; Agência Nacional de Águas","keywords":"Climatology; Streamflow; Flood myth; Environmental science; Magnitude (astronomy); Climate change; Climate model; Spatial ecology; Forcing (mathematics); Geography; Geology; Drainage basin; Cartography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003711096,0.0001033043,0.0001682942,0.00002222139,0.0002403456,0.00002101126,0.0001221874,0.00008660361,0.00001931913],"category_scores_gemma":[0.00002835225,0.00008388249,0.000009979002,0.0002428881,0.00037723,0.0003253419,0.0001623027,0.00007091846,0.0000169104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003805444,"about_ca_system_score_gemma":0.000006123149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007756618,"about_ca_topic_score_gemma":0.001797745,"domain_scores_codex":[0.9989831,0.0001166142,0.0001424749,0.0004220689,0.0001435877,0.0001921458],"domain_scores_gemma":[0.9997596,0.00004163455,0.00005918715,0.00005806121,0.00000341076,0.00007809563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002469659,0.000005102568,0.9924324,0.00002417275,0.000005161873,0.000008101855,0.001805947,0.003908937,0.000398684,0.0002953666,0.0001720711,0.0009194246],"study_design_scores_gemma":[0.0003071722,0.000289081,0.7100411,0.00003454139,0.00002797054,0.00000671685,0.0004933607,0.2864394,0.00004915252,0.001210317,0.0009278185,0.0001732937],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.969321,0.0008836511,0.0001658919,0.02892111,0.0001052285,0.000137135,0.000001872103,0.00003328908,0.0004307968],"genre_scores_gemma":[0.9974144,0.0002162663,0.0009149025,0.00134256,0.00007677944,0.00001538408,0.000001029243,0.000001592908,0.00001714995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2825305,"threshold_uncertainty_score":0.3420628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04001532127769657,"score_gpt":0.2206334891180196,"score_spread":0.180618167840323,"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."}}