{"id":"W2889183448","doi":"10.3390/ijerph15091892","title":"Spatial Patterns of Urban Wastewater Discharge and Treatment Plants Efficiency in China","year":2018,"lang":"en","type":"article","venue":"International Journal of Environmental Research and Public Health","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"China Scholarship Council","keywords":"Wastewater; Environmental science; Data envelopment analysis; Sewage treatment; Malmquist index; Inefficiency; Environmental engineering; Pollution; Beijing; Mainland China; Urbanization; China; Productivity; Geography; Economics; Total factor productivity; Economic growth","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":[0.0006379967,0.0001806939,0.0002353072,0.001931404,0.0002573384,0.0005630388,0.0003036032,0.0001882795,0.0005711796],"category_scores_gemma":[0.00117142,0.0002054972,0.0004135331,0.003603637,0.000428608,0.0003460036,0.0005299794,0.0001018814,0.00007714537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001753487,"about_ca_system_score_gemma":0.001123617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06606306,"about_ca_topic_score_gemma":0.0771768,"domain_scores_codex":[0.9995062,0.00007137237,0.00006257339,0.0001292552,0.0001187633,0.0001117476],"domain_scores_gemma":[0.9991704,0.0001963414,0.0002698259,0.00007172381,0.0002216659,0.00007008058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001149032,0.00004390566,0.9686105,0.00006097325,0.0001258915,0.0002876894,0.0008810891,0.01117141,0.002219556,0.001061275,0.0002941289,0.01512858],"study_design_scores_gemma":[0.000002857364,0.00001680251,0.9943453,0.000004320321,0.0000130897,0.00003341545,0.000338553,0.004554385,0.000231007,0.0001107918,0.0003391159,0.00001044928],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991812,0.00005276051,0.0001838089,0.00002075096,5.075123e-7,0.000004677833,0.0002013754,0.000005837107,0.0003490972],"genre_scores_gemma":[0.9993116,0.00004412405,0.0001712914,0.000002852782,8.712707e-7,0.000004808135,0.0002631843,0.000001075574,0.0002002367],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06606306,"threshold_uncertainty_score":0.131357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1003359182040953,"score_gpt":0.4224043576317497,"score_spread":0.3220684394276543,"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."}}