{"id":"W2537917590","doi":"10.15377/2410-3624.2016.03.01.3","title":"Water Security, The Nexus Of Water, Food, Population Growth and Energy","year":2016,"lang":"en","type":"article","venue":"The Global Environmental Engineers","topic":"Water-Energy-Food Nexus Studies","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Food security; Water security; Nexus (standard); Population growth; Population; Urbanization; Climate change; Food energy; Geography; Water supply; Environmental science; Water resource management; Environmental protection; Water resources; Natural resource economics; Agriculture; Ecology; Environmental health; Biology; Environmental engineering; Economics; Engineering","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":[0.0004914517,0.0002740186,0.000216032,0.001486394,0.001721932,0.002381052,0.0002618521,0.0005705438,0.005634076],"category_scores_gemma":[0.0006144804,0.0001399736,0.0002207639,0.002982889,0.00214781,0.003494582,0.002457625,0.001044211,0.000152533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002519083,"about_ca_system_score_gemma":0.003339548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0244864,"about_ca_topic_score_gemma":0.08247457,"domain_scores_codex":[0.9997781,0.00008886562,0.000007008585,0.00002375691,0.00003693267,0.00006535472],"domain_scores_gemma":[0.9996397,0.0001383906,0.00008490986,0.000009575627,0.00004818251,0.0000792122],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001281098,0.0001961313,0.2369077,0.001897383,0.0002457698,0.002629056,0.01691292,0.00258022,0.002934689,0.4790258,0.02612112,0.2304211],"study_design_scores_gemma":[0.00000927812,0.000234004,0.3901927,0.002345723,0.0001167182,0.0009816354,0.1531894,0.001455333,0.001099003,0.1603868,0.2899512,0.00003810277],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6228656,0.07452709,0.004779599,0.09779552,0.0005128137,0.0000971686,0.0007009593,0.00003438432,0.1986868],"genre_scores_gemma":[0.9542049,0.03685696,0.00144567,0.001472026,0.00007148026,0.00004488149,0.0001199689,0.000004567389,0.005779511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0244864,"threshold_uncertainty_score":0.04868776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003456529143508403,"score_gpt":0.1545081471180845,"score_spread":0.1510516179745761,"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."}}