{"id":"W2547873413","doi":"","title":"The Hydromet Decision Support System: operational applications in hydrometeorology and flash flood prediction","year":2006,"lang":"en","type":"article","venue":"33rd Conference on Radar Meteorology (6–10 August 2007)","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quantitative precipitation estimation; Hydrometeorology; Flash flood; Meteorology; Nowcasting; Radar; Quantitative precipitation forecast; Environmental science; Precipitation; Numerical weather prediction; Flood myth; Weather radar; Flood forecasting; Decision support system; Remote sensing; Computer science; Geography; Data mining","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001147947,0.0008709042,0.0008033274,0.0009190825,0.0003965854,0.001400854,0.0008311995,0.0006684226,0.01083219],"category_scores_gemma":[0.002882313,0.0002960197,0.0002597938,0.00149903,0.000290087,0.001184962,0.001073622,0.0008560213,0.003677787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004202969,"about_ca_system_score_gemma":0.0009340828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004040706,"about_ca_topic_score_gemma":0.002610804,"domain_scores_codex":[0.9995847,0.00009507623,0.00003945717,0.00008597503,0.0001570122,0.00003771534],"domain_scores_gemma":[0.9990908,0.0003710964,0.00008384368,0.0001171674,0.000218468,0.0001186937],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001001712,0.0003429643,0.01678351,0.0003931655,0.0001471078,0.0003341296,0.0002451649,0.08438157,0.01361877,0.009495321,0.1386463,0.7346102],"study_design_scores_gemma":[0.0003979911,0.0002309475,0.007173284,0.00009852352,0.0000558577,0.0001611579,0.00009322887,0.8680876,0.01092596,0.0127983,0.09991312,0.00006391195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1301615,0.003818763,0.6344689,0.004484784,0.0007281685,0.000976901,0.02709018,0.1613512,0.03691965],"genre_scores_gemma":[0.6756213,0.002049491,0.2803036,0.001040848,0.000548168,0.0006971858,0.02103269,0.001925884,0.0167808],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01083219,"threshold_uncertainty_score":0.0362373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01398779980311253,"score_gpt":0.2203565786736083,"score_spread":0.2063687788704958,"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."}}