{"id":"W2014391507","doi":"10.1007/s00376-006-0391-9","title":"Effects of heterogeneous vegetation on the surface hydrological cycle","year":2006,"lang":"en","type":"article","venue":"Advances in Atmospheric Sciences","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Environmental science; Evapotranspiration; Land cover; Watershed; Deciduous; Hydrology (agriculture); Water cycle; Structural basin; Drainage basin; Remote sensing; Land use; Geology; Geography","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":[0.0006928543,0.0002321773,0.0003237067,0.0004734963,0.000573811,0.0008038228,0.0002692396,0.0004162996,0.001602126],"category_scores_gemma":[0.00302359,0.0001999526,0.0004027633,0.0004085254,0.00109902,0.0006874583,0.0006915996,0.0003261794,0.0001034131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007773953,"about_ca_system_score_gemma":0.000271465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007655148,"about_ca_topic_score_gemma":0.008753907,"domain_scores_codex":[0.9996904,0.0001035909,0.000012808,0.00006286936,0.00003086217,0.00009953721],"domain_scores_gemma":[0.9975044,0.001767043,0.000196405,0.0001725671,0.00008096175,0.0002786073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004784387,0.0008177424,0.5522835,0.0001604217,0.0009308168,0.001729103,0.0004531339,0.2995454,0.09547169,0.006389649,0.0007431257,0.03669107],"study_design_scores_gemma":[0.0001742416,0.0003944945,0.8885686,0.00001081269,0.000305542,0.0003771095,0.0004998918,0.09945749,0.004399572,0.005044117,0.0007243503,0.00004374353],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988161,0.00008506683,0.0004499803,0.00003132029,0.000004819961,0.000002837027,0.00004529293,0.000007681736,0.0005568592],"genre_scores_gemma":[0.999793,0.00003098126,0.00008361002,0.000007132884,0.000005086696,9.387983e-7,0.00002300451,0.000003449388,0.0000527272],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007655148,"threshold_uncertainty_score":0.01522118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004653171571507729,"score_gpt":0.2204919762396196,"score_spread":0.2158388046681119,"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."}}