{"id":"W4406117541","doi":"10.5194/gmd-18-1-2025","title":"The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)","year":2025,"lang":"en","type":"article","venue":"Geoscientific model development","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Environment and Climate Change Canada","keywords":"Data assimilation; Modular design; Assimilation (phonology); Climate change; Meteorology; Environmental science; Climatology; Computer science; Geography; Operating system; Oceanography; Geology","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":[0.0007754773,0.0001250374,0.0001187825,0.00004538198,0.001180107,0.0001284805,0.0002401327,0.0000390743,0.00003891962],"category_scores_gemma":[0.00001715005,0.00007929264,0.00000718203,0.0001217296,0.00009482625,0.0001154555,0.0001915472,0.00006531847,0.00001326487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005736048,"about_ca_system_score_gemma":0.0001496191,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01545868,"about_ca_topic_score_gemma":0.2671449,"domain_scores_codex":[0.9986407,0.0000609611,0.0002648292,0.0004642616,0.0002720326,0.000297215],"domain_scores_gemma":[0.9993607,0.00009359181,0.00006069184,0.0003608562,0.00001908542,0.0001050398],"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":[0.0001295367,0.00003733175,0.3526687,0.0002457522,0.0001132779,0.00001608803,0.001129026,0.1882131,0.0000842456,0.003532733,0.005451828,0.4483784],"study_design_scores_gemma":[0.00008660432,0.000003369361,0.2142156,0.00001366693,0.00000850683,8.008933e-7,0.0000840418,0.755594,0.000005060162,0.00008428218,0.02982419,0.00007989818],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9837017,0.001673976,0.009877558,0.00076559,0.0007026897,0.0006216447,0.0006825766,0.00005664254,0.001917591],"genre_scores_gemma":[0.9956824,0.0001430107,0.002152306,0.0001442796,0.000008558211,0.000007290686,0.0007328517,0.000002333848,0.001127019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5673808,"threshold_uncertainty_score":0.9910975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04212535578931302,"score_gpt":0.2042955699843096,"score_spread":0.1621702141949966,"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."}}