{"id":"W2938446992","doi":"10.1175/jhm-d-18-0133.1","title":"Assimilation of Passive L-band Microwave Brightness Temperatures in the Canadian Land Data Assimilation System: Impacts on Short-Range Warm Season Numerical Weather Prediction","year":2019,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Canadian Space Agency","keywords":"Environmental science; Data assimilation; Daytime; Water content; Precipitation; Numerical weather prediction; Brightness temperature; Atmospheric sciences; Climatology; Brightness; Meteorology; Geology; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000764786,0.0001282409,0.0002841244,0.0001748987,0.00007822038,0.0000296112,0.0002890989,0.0001746757,0.00003516303],"category_scores_gemma":[0.00006492551,0.00007724498,0.0000559015,0.0002569607,0.0000710157,0.0002373131,0.00002631446,0.0003652603,0.00001188744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000323491,"about_ca_system_score_gemma":0.00006532583,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007559684,"about_ca_topic_score_gemma":0.06425074,"domain_scores_codex":[0.9984993,0.000304167,0.0003846207,0.0001979006,0.0003901404,0.0002239061],"domain_scores_gemma":[0.99914,0.0001442621,0.0002819934,0.0003117678,0.0000277932,0.00009421451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001565073,0.00006596902,0.9734696,0.00001985219,0.00005349579,0.00009719611,0.0008787943,0.00396491,0.01815806,0.000008407763,0.001492623,0.001634562],"study_design_scores_gemma":[0.0004773666,0.0003915218,0.9915443,0.00007369839,0.00005679046,0.0005419346,0.0001137807,0.004720468,0.001272659,0.00003717062,0.0006875764,0.00008270274],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923956,0.00006645972,0.00005543158,0.0009819182,0.0005015343,0.000205648,0.00001464007,0.000003976441,0.005774762],"genre_scores_gemma":[0.9994936,0.00001066088,0.00008869301,0.0002117643,0.0001395028,3.181878e-7,0.00002706913,0.00001108978,0.00001727807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05669106,"threshold_uncertainty_score":0.9990491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01405968408527476,"score_gpt":0.2376933834079937,"score_spread":0.2236336993227189,"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."}}