{"id":"W4315471737","doi":"10.1016/j.scs.2023.104401","title":"Urban ecosystem services supply-demand assessment from the perspective of the water-energy-food nexus","year":2023,"lang":"en","type":"article","venue":"Sustainable Cities and Society","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":98,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"Fundamental Research Funds for the Central Universities; China Scholarship Council; National Natural Science Foundation of China; National University's Basic Research Foundation of China; Jiangsu Office of Philosophy and Social Science","keywords":"Nexus (standard); Ecosystem services; Supply and demand; Production (economics); Natural resource economics; Environmental economics; Water supply; Business; Environmental science; Environmental resource management; Agricultural economics; Environmental engineering; Economics; Ecosystem; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004724433,0.0003313096,0.0002685817,0.001570098,0.0003875504,0.001803674,0.0003734058,0.0004544632,0.004721684],"category_scores_gemma":[0.001002243,0.0002119177,0.0004665316,0.003165821,0.0004878855,0.001126819,0.0009624487,0.0003790156,0.0002617677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003101151,"about_ca_system_score_gemma":0.001539198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03024176,"about_ca_topic_score_gemma":0.09074031,"domain_scores_codex":[0.9997012,0.0001177587,0.00001057996,0.00002292081,0.00009968031,0.00004790962],"domain_scores_gemma":[0.9996908,0.0001464977,0.0000276352,0.00001235343,0.00009310067,0.00002969366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003236289,0.0002884523,0.1367747,0.0003171284,0.0002940843,0.0005596268,0.0007493243,0.5766329,0.005531033,0.2287295,0.005855138,0.04394457],"study_design_scores_gemma":[0.00003001845,0.0001478871,0.08114491,0.00006414205,0.0001517689,0.0001769876,0.006408263,0.825102,0.002899907,0.0647923,0.01902823,0.00005354936],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9004704,0.0003319338,0.02117466,0.001681839,0.00002061263,0.0000815683,0.003146051,0.00004260596,0.07305025],"genre_scores_gemma":[0.9933012,0.0001443286,0.002654037,0.00004033435,0.000008600038,0.00002300155,0.00043956,0.00001204119,0.003376915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03024176,"threshold_uncertainty_score":0.06013149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004044321084228087,"score_gpt":0.1905554058130472,"score_spread":0.1865110847288191,"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."}}