{"id":"W7160577180","doi":"","title":"Water Yield Monitoring of Brush Management in Texas","year":2010,"lang":"en","type":"dissertation","venue":"ThinkTech (Texas Tech University)","topic":"Water Quality and Resources Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hydrology (agriculture); Precipitation; Watershed; Streamflow; Current (fluid); Surface runoff; Stream flow; Drainage basin; Surface water","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001904209,0.0001312636,0.0000891336,0.0007235583,0.0004310733,0.0004439972,0.0003068012,0.0001006538,0.001191185],"category_scores_gemma":[0.0004843079,0.00006928352,0.00009297537,0.001305368,0.0001611295,0.000250318,0.0003156054,0.0001462542,0.0001562017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001447768,"about_ca_system_score_gemma":0.000858016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07471523,"about_ca_topic_score_gemma":0.198383,"domain_scores_codex":[0.9998727,0.0000102069,0.000007976526,0.00003868098,0.00004642182,0.00002400257],"domain_scores_gemma":[0.999631,0.00003015759,0.0001057716,0.00001879193,0.0001657943,0.00004845271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001055309,0.0001038691,0.9301115,0.00004447071,0.00002294682,0.0002365707,0.001163637,0.002354639,0.00740962,0.0002772222,0.002238173,0.05593168],"study_design_scores_gemma":[0.000004053222,0.00008316977,0.9908431,0.00001164502,0.00001084341,0.00004232776,0.001419544,0.003139215,0.001632329,0.00007510194,0.002732845,0.000005762702],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939774,0.0000431321,0.0006086195,0.00006245484,0.000003833928,0.00002641311,0.0007664887,0.00003814673,0.004473574],"genre_scores_gemma":[0.9958295,0.0001276291,0.0009800604,0.00001386112,0.000005654075,0.00002015693,0.001018044,0.00000686885,0.001998016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07471523,"threshold_uncertainty_score":0.1485606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02445651089948234,"score_gpt":0.216295387253539,"score_spread":0.1918388763540567,"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."}}