{"id":"W2094892075","doi":"10.1175/jhm527.1","title":"Time Scales of Land Surface Hydrology","year":2006,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Aeronautics and Space Administration; National Science Foundation","keywords":"Evapotranspiration; Environmental science; Hydrology (agriculture); Precipitation; Vegetation (pathology); Water content; Forcing (mathematics); Water cycle; Soil water; DNS root zone; Scale (ratio); Soil science; Geology; Atmospheric sciences; Meteorology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0002655008,0.00009721751,0.0001050696,0.0002027303,0.0001380753,0.0005238451,0.0002119668,0.0002345599,0.003186451],"category_scores_gemma":[0.001723035,0.000100122,0.0002075715,0.0002266917,0.0002452306,0.0009922392,0.0003769195,0.0004157945,0.0001489095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004868282,"about_ca_system_score_gemma":0.0001799336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002481918,"about_ca_topic_score_gemma":0.0009142464,"domain_scores_codex":[0.9999448,0.000008562075,0.000002770927,0.00001889989,0.00001485229,0.00001013967],"domain_scores_gemma":[0.9995044,0.0002769124,0.00007537261,0.00003691158,0.00005185459,0.00005448595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003336526,0.0001369115,0.140219,0.0003093734,0.0002301706,0.0008366675,0.0007144579,0.3698916,0.05384424,0.3580015,0.007738132,0.06774426],"study_design_scores_gemma":[0.00004380013,0.00005107766,0.2220833,0.00002756934,0.00005478484,0.0001287133,0.0002624819,0.6492109,0.005157445,0.1122383,0.01069288,0.0000487161],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9003816,0.00145602,0.06951625,0.001976916,0.0001110407,0.00004758035,0.00130635,0.0004414974,0.02476272],"genre_scores_gemma":[0.9978607,0.0001533966,0.001004615,0.00002024135,0.00001924086,0.000008514386,0.0001089042,0.00001942835,0.0008048062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003186451,"threshold_uncertainty_score":0.01065981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004519697558752836,"score_gpt":0.1985688831079313,"score_spread":0.1940491855491784,"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."}}