{"id":"W2026992547","doi":"10.1007/s00024-012-0520-6","title":"An Experimental High-Resolution Forecast System During the Vancouver 2010 Winter Olympic and Paralympic Games","year":2012,"lang":"en","type":"article","venue":"Pure and Applied Geophysics","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Meteorology; Mesoscale meteorology; Visibility; Environmental science; Terrain; Numerical weather prediction; Squall line; Wind speed; Weather Research and Forecasting Model; Snow; Cloud cover; Precipitation; Climatology; Geology; Cloud computing; Geography; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000836055,0.0001167514,0.0001240929,0.00001568998,0.0003132357,0.00005235494,0.00007094655,0.00004674211,0.0001058588],"category_scores_gemma":[9.401656e-7,0.00007053652,0.00002021279,0.00005888095,0.00008426626,0.0002057735,0.00001499072,0.00007548474,0.00003059359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003787753,"about_ca_system_score_gemma":0.000003204154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008661933,"about_ca_topic_score_gemma":0.00007498249,"domain_scores_codex":[0.9993432,0.00002894972,0.0001100507,0.0001619763,0.0001064286,0.0002493713],"domain_scores_gemma":[0.9996578,0.00004753883,0.00004335115,0.0001291208,0.000006488091,0.0001157271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006986305,0.0004661625,0.8460483,0.000301739,0.0002148262,0.000006715773,0.01157297,0.01580248,0.02307772,0.04126809,0.001181953,0.05936038],"study_design_scores_gemma":[0.0004229849,0.00008756427,0.9913955,0.000005539386,0.0000294686,0.000004230385,0.001218014,0.004191621,0.0006776697,0.001332191,0.0004398042,0.0001953649],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973301,0.000562762,0.00007066375,0.00001792905,0.000233288,0.0001630697,0.0000192499,0.00003184585,0.00157107],"genre_scores_gemma":[0.9992943,0.000006565073,0.0000988458,0.00008716597,0.0003746241,0.00000691471,0.00002798992,0.000003178217,0.0001004141],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1453472,"threshold_uncertainty_score":0.2876396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01120217785558303,"score_gpt":0.1980448171726076,"score_spread":0.1868426393170246,"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."}}