{"id":"W2025214147","doi":"10.1175/2007jhm810.1","title":"The MAGS Water and Energy Budget Study","year":2008,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate variability and models","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Environment and Climate Change Canada","funders":"National Aeronautics and Space Administration","keywords":"Environmental science; Energy budget; Climatology; Surface runoff; Data assimilation; Water cycle; Meteorology; Climate model; Climate change; Geography","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":[0.0002216096,0.0001281004,0.0001074014,0.0006796576,0.0002864231,0.0005111397,0.0002215061,0.0001558474,0.003585665],"category_scores_gemma":[0.0004497577,0.00006810234,0.0001691259,0.0008840853,0.00009101965,0.0004056038,0.0003643673,0.0002348519,0.0005841528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002222232,"about_ca_system_score_gemma":0.001780851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.132666,"about_ca_topic_score_gemma":0.2705405,"domain_scores_codex":[0.9999207,0.00001167534,0.000005036667,0.00001551918,0.00002452634,0.00002253086],"domain_scores_gemma":[0.9998957,0.00001205126,0.00001825577,0.00001386612,0.00003515028,0.00002499333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009142473,0.0003271776,0.6384254,0.0005332699,0.000334153,0.001664447,0.001158483,0.008987995,0.005220556,0.02966392,0.1243497,0.1884207],"study_design_scores_gemma":[0.00005193657,0.00008250702,0.7252695,0.00009555167,0.00007944269,0.0001810056,0.001104134,0.007956445,0.002545082,0.001551403,0.2610642,0.00001870457],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8525215,0.001714641,0.0008190057,0.003017087,0.0001211101,0.0001081429,0.06550006,0.0002172688,0.07598115],"genre_scores_gemma":[0.9652898,0.000619359,0.001157483,0.0003497656,0.00006058294,0.00005763172,0.01270476,0.00002963787,0.01973103],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.132666,"threshold_uncertainty_score":0.2637875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01198210811876312,"score_gpt":0.2171873296274256,"score_spread":0.2052052215086624,"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."}}