{"id":"W4399787101","doi":"10.1016/j.jhydrol.2024.131530","title":"Modelling the impacts of future droughts and post-droughts on hydrology, crop yields, and their linkages through assessing virtual water trade in agricultural watersheds of high-latitude regions","year":2024,"lang":"en","type":"article","venue":"Journal of Hydrology","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Environmental science; Virtual water; Agriculture; Cropping; Precipitation; Climate change; Watershed; Temperate climate; Water resources; Hydrology (agriculture); Farm water; Water resource management; Water scarcity; Water conservation; Geography; Ecology; Geology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0004585813,0.0004350419,0.0003063433,0.0003231554,0.0003620542,0.001140855,0.0005800939,0.00107406,0.0007768198],"category_scores_gemma":[0.001260036,0.000342093,0.0006914506,0.0006167302,0.0005024595,0.000988255,0.0006499899,0.00058802,0.00005943601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001356015,"about_ca_system_score_gemma":0.001589345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08135798,"about_ca_topic_score_gemma":0.06453798,"domain_scores_codex":[0.9998312,0.00004748329,0.00001231122,0.00004872034,0.0000176079,0.00004261842],"domain_scores_gemma":[0.9996295,0.0001831489,0.00006241326,0.00002617251,0.00004890083,0.00004985666],"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":[0.00002406291,0.00003208876,0.01529614,0.00001266552,0.00003397274,0.00005751907,0.00003457823,0.9815746,0.0006748563,0.0006885467,0.00007561561,0.00149543],"study_design_scores_gemma":[0.00001165566,0.00002505211,0.00636462,0.000002637388,0.00001579556,0.000009264747,0.00007845119,0.9924068,0.0002475154,0.000615275,0.0002157143,0.000007222601],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9856501,0.00008443149,0.01171273,0.0001731693,0.00001636765,0.00002557243,0.0004972329,0.00007353944,0.001766855],"genre_scores_gemma":[0.9976966,0.00006807962,0.001615784,0.00001028735,0.000003308856,0.00001389519,0.0002021895,0.000006705103,0.0003831685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08135798,"threshold_uncertainty_score":0.1617689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009895905105516535,"score_gpt":0.2319011517282925,"score_spread":0.2220052466227759,"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."}}