{"id":"W2914657599","doi":"10.12783/dteees/iceee2018/27910","title":"Ecological Network Analysis for Water Embodied in Global Agricultural Products Trade","year":2019,"lang":"en","type":"article","venue":"DEStech Transactions on Environment Energy and Earth Science","topic":"Sustainability and Ecological Systems Analysis","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Embodied cognition; European union; Redistribution (election); Business; China; Natural resource economics; International trade; Economics; Ecology; Geography; Political science; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006493274,0.0004280791,0.0002404481,0.001841491,0.0003896219,0.0009080441,0.0003771468,0.0005367185,0.003594494],"category_scores_gemma":[0.002421703,0.0001602447,0.0008694776,0.001888067,0.0003829791,0.00156761,0.0007514635,0.0003871768,0.0001831595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001511271,"about_ca_system_score_gemma":0.0006245307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0189611,"about_ca_topic_score_gemma":0.01216392,"domain_scores_codex":[0.9997602,0.0001201654,0.00001012189,0.00004888037,0.00002931275,0.00003126655],"domain_scores_gemma":[0.9992717,0.0004592055,0.0001277175,0.00003715144,0.00006795943,0.00003629611],"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":[0.00002058024,0.00001969645,0.01168883,0.00002174836,0.00005086764,0.00006555854,0.00004417228,0.9559968,0.0002915651,0.02647389,0.0003533648,0.004972892],"study_design_scores_gemma":[0.000002441458,0.000009979236,0.003787662,0.000006043806,0.00001454665,0.00001862376,0.00005801499,0.9819359,0.0000638683,0.01340489,0.0006922855,0.000005758961],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7363295,0.0006393169,0.2413062,0.001084868,0.00003433206,0.00008207675,0.002579368,0.0001488601,0.01779553],"genre_scores_gemma":[0.9806932,0.0004396155,0.01546276,0.00003629938,0.00001291353,0.00005876114,0.0006594684,0.00002131124,0.002615689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0189611,"threshold_uncertainty_score":0.03770149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006235321435274307,"score_gpt":0.1841939663471675,"score_spread":0.1779586449118932,"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."}}