{"id":"W3013909215","doi":"10.1016/j.scitotenv.2020.138155","title":"Spatial-temporal assessment of agricultural virtual water and uncertainty analysis: The case of Kazakhstan (2000–2016)","year":2020,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Water-Energy-Food Nexus Studies","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Agriculture; Environmental science; Water resource management; Environmental resource management; Geography; Environmental planning; Environmental protection; Archaeology","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":[0.00107567,0.0002535675,0.0002260989,0.001738494,0.000526838,0.001706541,0.0005998642,0.0005514012,0.001438424],"category_scores_gemma":[0.001983449,0.0001581793,0.0006015412,0.004254957,0.0006308768,0.001244501,0.0009936459,0.0003778597,0.000124832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003527229,"about_ca_system_score_gemma":0.001916714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2086508,"about_ca_topic_score_gemma":0.1880234,"domain_scores_codex":[0.9996854,0.00007884387,0.00002803907,0.00004494655,0.00005881079,0.0001040093],"domain_scores_gemma":[0.9993379,0.0001720822,0.0001589209,0.00004844469,0.0002335372,0.00004924139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008230804,0.0002134482,0.4912802,0.0002916378,0.0005516965,0.003497965,0.001940674,0.4243745,0.002864456,0.02045844,0.005478076,0.04822579],"study_design_scores_gemma":[0.00003291158,0.0001316409,0.5796593,0.0001136811,0.0003305193,0.000524482,0.009393972,0.3865923,0.002608842,0.006698403,0.01381994,0.00009404867],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951161,0.0003263955,0.0007743022,0.0003348091,0.00001087236,0.000006135618,0.001161422,0.00002694705,0.002242917],"genre_scores_gemma":[0.9986998,0.0001098696,0.0003952115,0.00000836701,0.000003000103,0.000003056067,0.0004237494,0.000002854338,0.0003540409],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2086508,"threshold_uncertainty_score":0.4148727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009388166909795612,"score_gpt":0.207084494814899,"score_spread":0.1976963279051034,"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."}}