{"id":"W2027656870","doi":"10.1007/s11269-014-0618-y","title":"A Virtual Water Assessment Methodology for Cropping Pattern Investigation","year":2014,"lang":"en","type":"article","venue":"Water Resources Management","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Virtual water; Cropping; Environmental science; Water use; Current (fluid); Agricultural engineering; Crop; Hydrogeology; Arid; Water resource management; Water resources; Water scarcity; Agriculture; Geography; Agronomy; Engineering; Geology; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001556953,0.0001998556,0.0001886739,0.0000525065,0.0002366471,0.00007533781,0.0002758855,0.00006040926,0.001058497],"category_scores_gemma":[0.00001009966,0.0001248441,0.00008814681,0.00003781815,0.0002119585,0.0001710688,0.0006630993,0.00008953215,0.0002704165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003022111,"about_ca_system_score_gemma":5.542174e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002191306,"about_ca_topic_score_gemma":0.00002761226,"domain_scores_codex":[0.998082,0.0003175169,0.0002832834,0.0004650344,0.0002837202,0.0005684156],"domain_scores_gemma":[0.9994136,0.00004316494,0.00004262961,0.0003750223,0.000003653595,0.0001219108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002186488,0.0005783599,0.3217999,0.0005678345,0.0003427801,0.0000305496,0.04327219,0.02466736,0.1851829,0.001139461,0.003749119,0.4184509],"study_design_scores_gemma":[0.002172404,0.0009310808,0.3186339,0.00002804468,0.0001611886,0.000005611859,0.002840161,0.01146964,0.07812604,0.01579824,0.5689035,0.0009301535],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8841191,0.000001446677,0.1085129,0.001176707,0.0000981136,0.000648851,0.000001533318,0.00005295324,0.0053884],"genre_scores_gemma":[0.9862931,0.000001394149,0.007644614,0.001355952,0.00005907074,0.0001876592,0.00004484579,0.00002501757,0.004388385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5651544,"threshold_uncertainty_score":0.9998547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.025542800237618,"score_gpt":0.2711868657725346,"score_spread":0.2456440655349166,"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."}}