{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007721471,0.00007297261,0.0001628588,0.00003155517,0.000220431,0.00001027217,0.0001893644,0.00004190944,0.0003867275],"category_scores_gemma":[0.00003572508,0.00003620603,0.00004382305,0.00005064519,0.0003103288,0.000117111,0.0001655576,0.0001266768,0.00002046231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002976711,"about_ca_system_score_gemma":0.000005082213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001025455,"about_ca_topic_score_gemma":0.00008917847,"domain_scores_codex":[0.9990714,0.0001549944,0.0002848044,0.0001063331,0.0001782995,0.0002041778],"domain_scores_gemma":[0.9995635,0.0001247134,0.00008788171,0.0001421901,0.00000927813,0.00007241756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001280295,0.002980117,0.8048013,0.00001065127,0.0005027602,0.001857507,0.01838955,0.006662409,0.1263343,0.001034249,0.01720966,0.01893722],"study_design_scores_gemma":[0.005108978,0.01053653,0.4115055,0.000006072462,0.0002229133,0.01537555,0.0008952589,0.003622215,0.003890114,0.02853994,0.5196782,0.0006187815],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966935,0.00006706429,0.00005102849,0.001718636,0.0001860193,0.00003061842,4.241269e-7,0.000003530076,0.001249217],"genre_scores_gemma":[0.9987884,0.0002079808,0.0001018352,0.0002646648,0.00003539389,0.000001864094,2.140556e-7,0.000005097255,0.0005945693],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5024685,"threshold_uncertainty_score":0.4234395,"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."}}