{"id":"W2382038818","doi":"","title":"Application of WRMM model toUrumqi river water resource management","year":2005,"lang":"en","type":"article","venue":"Journal of Xinjiang Agricultural University","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Arid; Water resource management; Drainage basin; Irrigation; Environmental science; Water resources; Resource (disambiguation); Channel (broadcasting); Hydrology (agriculture); Drainage; Natural resource; Computer science; Geology; Geography; Ecology","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":[0.0003463403,0.0005010484,0.000446198,0.0003428174,0.0005295607,0.0005326655,0.001328446,0.0006360863,0.003069573],"category_scores_gemma":[0.00108183,0.0003371538,0.0006142257,0.000844648,0.0001594913,0.0005125634,0.0004730553,0.0004277605,0.000326658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002145664,"about_ca_system_score_gemma":0.00272763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3683473,"about_ca_topic_score_gemma":0.2129605,"domain_scores_codex":[0.9997895,0.00006413338,0.00001151949,0.00004518225,0.00004760564,0.00004208859],"domain_scores_gemma":[0.999701,0.00005993702,0.0000213318,0.00002735695,0.000161578,0.00002883197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000173331,0.00001644076,0.0031198,0.00002772792,0.00001979606,0.00005364423,0.00003100764,0.9895229,0.0005152487,0.0007389822,0.0009832956,0.004953869],"study_design_scores_gemma":[0.00001154514,0.000006784231,0.0008817252,0.000003048261,0.000006141621,0.000006628231,0.0000168413,0.9976756,0.0002750984,0.0002023583,0.0009076655,0.000006545171],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8365068,0.0004563188,0.104281,0.001492743,0.0001774551,0.0002543892,0.01059115,0.003767279,0.04247293],"genre_scores_gemma":[0.9702625,0.000229909,0.02126992,0.00006414381,0.00001779751,0.0001421518,0.003063577,0.0001273147,0.004822739],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3683473,"threshold_uncertainty_score":0.7324065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005874888829887382,"score_gpt":0.197760184074416,"score_spread":0.1918852952445286,"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."}}