{"id":"W3162774041","doi":"10.1016/j.seps.2021.101082","title":"Environmental performance evaluation: A state-level DEA analysis","year":2021,"lang":"en","type":"article","venue":"Socio-Economic Planning Sciences","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Data envelopment analysis; Environmental economics; State (computer science); Perspective (graphical); Computer science; Environmental pollution; Energy consumption; Consumption (sociology); Business; Risk analysis (engineering); Environmental resource management; Economics; Environmental protection; Engineering; Environmental science; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0118774,0.0002301848,0.0005300994,0.0007302209,0.001305169,0.0008538997,0.001323353,0.00008271853,0.002925352],"category_scores_gemma":[0.000729557,0.0001962273,0.0003784755,0.002121507,0.0009160688,0.0009183939,0.0002449119,0.00017928,0.001198435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000403706,"about_ca_system_score_gemma":0.0008582821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004261786,"about_ca_topic_score_gemma":0.00004404194,"domain_scores_codex":[0.9946169,0.0004807068,0.0009373412,0.00128404,0.002132914,0.0005480908],"domain_scores_gemma":[0.9973298,0.001175146,0.0005285881,0.0007095162,0.0001071118,0.0001498522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003890759,0.00003377907,0.5437099,7.44093e-7,0.0001538004,0.00000720778,0.00172019,0.4393249,0.0002199029,0.00008995979,0.0007660296,0.01396964],"study_design_scores_gemma":[0.0002595589,0.00004555413,0.4281885,0.00001017747,0.0003095306,0.000013788,0.008014741,0.5576111,0.0005806077,0.003086943,0.001503504,0.0003760165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989844,0.0007022357,0.002009173,0.0007408462,0.0004301953,0.00008980199,0.00007236192,0.00003545624,0.006075889],"genre_scores_gemma":[0.9959652,0.00002248949,0.001898681,0.0002954024,0.00008191126,0.00001195217,0.00002435953,0.00000751692,0.001692533],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1182862,"threshold_uncertainty_score":0.999995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1666685245609271,"score_gpt":0.3978310177766515,"score_spread":0.2311624932157244,"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."}}