{"id":"W2519117470","doi":"10.1175/waf-d-16-0035.1","title":"The Pan-Canadian High Resolution (2.5 km) Deterministic Prediction System","year":2016,"lang":"en","type":"article","venue":"Weather and Forecasting","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":235,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Numerical weather prediction; Meteorology; Global Forecast System; Environmental science; Data assimilation; Precipitation; Weather forecasting; Quantitative precipitation forecast; Model output statistics; Grid; High resolution; Relative humidity; Remote sensing; Geology; Geography; Geodesy","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":[0.0003321002,0.00006355461,0.0000666184,0.00002920908,0.0006388291,0.00005052962,0.00006178294,0.00004119993,0.0001615179],"category_scores_gemma":[0.0001008868,0.00002945643,0.0000189181,0.00005567781,0.00006532299,0.00007244461,0.000004232862,0.00003872513,0.00005141483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009248542,"about_ca_system_score_gemma":0.00001737333,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.008298065,"about_ca_topic_score_gemma":0.02481588,"domain_scores_codex":[0.9993538,0.00005906943,0.0001471521,0.0001317795,0.00008129465,0.0002268737],"domain_scores_gemma":[0.99934,0.0004030272,0.00003971812,0.00008647722,0.00001804419,0.0001127428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00003287886,0.000002153732,0.3203825,0.00001086871,0.00001394921,0.000006446083,0.0001123254,0.0005449679,0.00005156382,0.004358022,0.00008013763,0.6744041],"study_design_scores_gemma":[0.0002431577,0.0001449171,0.8894242,0.00004076166,0.00001523563,0.00002095049,0.0001300189,0.09954898,0.00000251094,0.003961347,0.006364553,0.0001033429],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9644597,0.0003544023,0.001402056,0.0002713648,0.0003873275,0.0001689485,0.0001955312,0.00005323689,0.03270749],"genre_scores_gemma":[0.9992867,0.00001329845,0.0001265211,0.00002972121,0.0001447684,0.000001769095,0.00001170477,0.000001954777,0.0003835329],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6743008,"threshold_uncertainty_score":0.9983057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03113107117173858,"score_gpt":0.1936673673751409,"score_spread":0.1625362962034023,"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."}}