{"id":"W1973006090","doi":"10.1007/s00024-012-0553-x","title":"Adaptive Blending of Model and Observations for Automated Short-Range Forecasting: Examples from the Vancouver 2010 Olympic and Paralympic Winter Games","year":2012,"lang":"en","type":"article","venue":"Pure and Applied Geophysics","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Nowcasting; Meteorology; Numerical weather prediction; Extrapolation; Environmental science; Terrain; Wind speed; Range (aeronautics); Visibility; Climatology; Relative humidity; Computer science; Geography; Statistics; Mathematics; Geology; Cartography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007901848,0.0006355728,0.0004823212,0.0005348078,0.0007729999,0.0009394403,0.00079425,0.0007550807,0.0009910177],"category_scores_gemma":[0.002178473,0.0003631039,0.0003312663,0.001149412,0.0003600507,0.0006277565,0.0005904433,0.0009068854,0.0002428061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009828841,"about_ca_system_score_gemma":0.0009715756,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3979852,"about_ca_topic_score_gemma":0.5500571,"domain_scores_codex":[0.9997581,0.00007159708,0.00001317449,0.00004780212,0.00006851088,0.00004081708],"domain_scores_gemma":[0.9992094,0.0003589619,0.00002898504,0.00009302398,0.0002558046,0.00005382706],"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":[0.0007441192,0.0004767538,0.06177694,0.0001441438,0.0002066595,0.0008074666,0.0005574665,0.7693164,0.005889904,0.001685375,0.009809582,0.1485853],"study_design_scores_gemma":[0.00005194571,0.00004350542,0.02449764,0.00001019725,0.00003646058,0.00004280447,0.0002229472,0.9688723,0.002156052,0.001044694,0.002994356,0.00002710688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9530482,0.0006421995,0.03246876,0.001045767,0.00009686298,0.0000767142,0.00126198,0.001361237,0.009998251],"genre_scores_gemma":[0.9840111,0.0001527411,0.01321336,0.00003030636,0.00001127427,0.00001128661,0.0007297323,0.00008629009,0.001753891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6020148,"threshold_uncertainty_score":0.7913374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09929685485464707,"score_gpt":0.2401491898669771,"score_spread":0.14085233501233,"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."}}