{"id":"W2623592481","doi":"10.1002/eco.1879","title":"Litter is more effective than forest canopy reducing soil evaporation in Dry Chaco rangelands","year":2017,"lang":"en","type":"article","venue":"Ecohydrology","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre; Agencia Nacional de Promoción Científica y Tecnológica; Secretaría de Ciencia y Técnica, Universidad de Buenos Aires; Universidad de Buenos Aires; Inter-American Institute for Global Change Research; National Science Foundation","keywords":"Lysimeter; Environmental science; Litter; Canopy; Plant litter; Transpiration; Tree canopy; Hydrology (agriculture); Soil water; Agronomy; Ecosystem; Soil science; Ecology; Geology; Botany; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001821125,0.0001033509,0.0001320937,0.00005258919,0.0001762436,0.00003327881,0.0001957918,0.0001314608,0.000354185],"category_scores_gemma":[0.00001399675,0.00009398752,0.00003529029,0.00004587761,0.0001316083,0.0002162027,0.00009572198,0.0001392781,0.0002299174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008937508,"about_ca_system_score_gemma":0.000006029985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002113994,"about_ca_topic_score_gemma":0.005946155,"domain_scores_codex":[0.9992355,0.00004518489,0.0001327959,0.0002688034,0.00008713036,0.0002305953],"domain_scores_gemma":[0.9995203,0.00002330674,0.00008672161,0.0003240004,0.000002371403,0.00004331199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004068455,0.00002637247,0.9460396,0.000002613231,0.000009162244,0.00002605251,0.001123345,0.04827224,0.001729986,0.0000102517,0.0001012991,0.002618345],"study_design_scores_gemma":[0.0004531567,0.00005377892,0.6349009,0.000007835148,0.000008661173,0.00001043261,0.000001758184,0.3621321,0.0003331631,0.00123499,0.0007445793,0.000118643],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908552,0.00001587407,0.00003038858,0.001303678,0.0001470944,0.0001829426,0.00001335944,0.00001447289,0.007437061],"genre_scores_gemma":[0.9987141,0.00001866785,0.00004035913,0.0002193906,0.00003579928,0.00004525701,0.0000398911,0.000009583398,0.0008769604],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3138599,"threshold_uncertainty_score":0.3878078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00503716138969603,"score_gpt":0.2217928000550551,"score_spread":0.2167556386653591,"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."}}