{"id":"W2294417786","doi":"10.5539/mas.v10n5p49","title":"An Application of WEAP Model in Water Resources Management Considering the Environmental Scenarios and Economic Assessment Case Study: Hirmand Catchment","year":2016,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Water resources management and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental science; Agriculture; Ecosystem; Drainage basin; Wetland; Vegetation (pathology); Water resource management; Environmental resource management; Environmental protection; Geography; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0005634852,0.0006498388,0.0007214181,0.0006992399,0.0005904047,0.001438307,0.000862935,0.001370584,0.004341599],"category_scores_gemma":[0.00114187,0.0002755543,0.0007221843,0.0008809218,0.0003552161,0.0007132075,0.0007744429,0.0007316624,0.0001372049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001639144,"about_ca_system_score_gemma":0.001491321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05916109,"about_ca_topic_score_gemma":0.03808822,"domain_scores_codex":[0.9998191,0.00007499969,0.000008059643,0.00002489598,0.00002450671,0.0000484251],"domain_scores_gemma":[0.9995454,0.0002680529,0.00003286482,0.00001458995,0.00009392347,0.00004510157],"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":[0.0000521765,0.00005783591,0.002629795,0.00002457902,0.00001449121,0.0001918179,0.0000173206,0.9909032,0.0002294755,0.002250857,0.0005418675,0.003086565],"study_design_scores_gemma":[0.00002108833,0.00003136924,0.0006862322,0.00000432781,0.00001082602,0.00001297226,0.00006107589,0.9981552,0.0001041377,0.0005907408,0.0003168342,0.000005247019],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9344293,0.0003149719,0.02992041,0.001231462,0.00007603726,0.0001545275,0.001331639,0.0002786903,0.03226293],"genre_scores_gemma":[0.9910458,0.0001516575,0.005354469,0.00003396951,0.00001442014,0.00007724662,0.0002914101,0.00001938445,0.003011615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05916109,"threshold_uncertainty_score":0.1176335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007537899959182995,"score_gpt":0.2118109870823335,"score_spread":0.2042730871231505,"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."}}