{"id":"W2350204246","doi":"","title":"Study on Indices and Development Model of Water Saving Irrigation","year":2003,"lang":"en","type":"article","venue":"Jieshui guan'gai","topic":"Research studies in Vietnam","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Irrigation; Water resource management; Loan; Water development; Agriculture; Water resources; Irrigation statistics; Agricultural development; Irrigation management; Process (computing); Water saving; Water conservation; Business; Environmental science; Farm water; Environmental planning; Agricultural economics; Economics; Geography; Computer science; Finance","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":[0.0009341768,0.0004246947,0.0002760034,0.0008367387,0.0002847372,0.001544741,0.0007328064,0.0003956772,0.002447165],"category_scores_gemma":[0.001944747,0.0001863851,0.0004287114,0.001002725,0.0003248338,0.001529713,0.0003431847,0.0006031549,0.0003812563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000991418,"about_ca_system_score_gemma":0.0008145769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007747863,"about_ca_topic_score_gemma":0.004944107,"domain_scores_codex":[0.9996488,0.0001398457,0.00001654287,0.00005998037,0.0001018133,0.00003307071],"domain_scores_gemma":[0.9996307,0.000146656,0.00003446206,0.00001689684,0.0001505177,0.00002080418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006514524,0.00007782645,0.01532169,0.0001589935,0.00006392921,0.0002212087,0.0005972789,0.6987032,0.002374419,0.1647757,0.006915568,0.1107249],"study_design_scores_gemma":[0.000004285341,0.00003742323,0.001367315,0.00001281025,0.00001019677,0.00003807358,0.00009043609,0.9855592,0.0005198043,0.009481103,0.002871145,0.000008197837],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1821603,0.000940024,0.7564537,0.001012333,0.0001069751,0.0001331777,0.000381422,0.0005186357,0.05829338],"genre_scores_gemma":[0.9453593,0.000603135,0.0445122,0.00002862606,0.00002901149,0.0001323147,0.0003461339,0.00005975784,0.00892958],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007747863,"threshold_uncertainty_score":0.01540554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0458056089102101,"score_gpt":0.2962442605384008,"score_spread":0.2504386516281907,"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."}}