{"id":"W3021105347","doi":"10.3968/11540","title":"Research on Sustainable Development of Xi’an City Based on ecological Footprint Model","year":2020,"lang":"en","type":"article","venue":"Canadian social science","topic":"Water Resources and Sustainability","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ecological footprint; Per capita; Ecological deficit; Sustainable development; Carrying capacity; Investment (military); Ecology; Natural resource economics; Geography; Environmental science; Economics; Population; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001920868,0.00009447926,0.0001189503,0.00009208717,0.001257109,0.00006623393,0.0007798302,0.00007080454,0.0003623221],"category_scores_gemma":[0.0002426256,0.00008273773,0.0000325957,0.00106239,0.001293481,0.00009053619,0.000211819,0.0002380533,0.00003307327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002849507,"about_ca_system_score_gemma":0.001095118,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01021073,"about_ca_topic_score_gemma":0.007946612,"domain_scores_codex":[0.9974627,0.0001027176,0.0001607695,0.000511871,0.0008673502,0.000894537],"domain_scores_gemma":[0.998761,0.00003351396,0.00002988614,0.0001833766,0.00007136863,0.0009208825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006919729,0.002117493,0.3950478,0.0002444055,0.00001536751,0.0005241254,0.1173095,0.2517105,0.007837189,0.1240646,0.005128697,0.0953083],"study_design_scores_gemma":[0.0007459255,0.001511852,0.6690066,0.00001250824,0.000004938518,3.915169e-7,0.0429826,0.2035271,0.009620226,0.006155717,0.06553788,0.0008943191],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8923116,3.380072e-7,0.0001111874,0.00180974,0.000009441502,0.0002590415,0.000003193794,0.00001239522,0.105483],"genre_scores_gemma":[0.9983625,5.675972e-8,0.0004536806,0.000935816,0.00001980897,0.00001758735,9.64831e-7,0.000004888328,0.0002046395],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2739587,"threshold_uncertainty_score":0.9963804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07393157617411704,"score_gpt":0.3111166730863771,"score_spread":0.23718509691226,"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."}}