{"id":"W3157623802","doi":"10.3390/su13094913","title":"Achieving Socioeconomic Development Fuelled by Globalization: An Analysis of 146 Countries","year":2021,"lang":"en","type":"article","venue":"Sustainability","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"National Natural Science Foundation of China","keywords":"Globalization; Lagging; Data envelopment analysis; Socioeconomic status; Productivity; Socioeconomic development; Poverty; Economic globalization; Economics; Developing country; Index (typography); Development economics; Economic growth; Computer science; Sociology; Statistics; Market economy; Population; Mathematics","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":[0.001293061,0.0002429052,0.0003201469,0.002144232,0.0004179556,0.0009435491,0.0002041218,0.0002439849,0.00100212],"category_scores_gemma":[0.002147562,0.0001790911,0.0008701585,0.005323659,0.0004872188,0.0005480792,0.001041239,0.0003546816,0.0001745961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006572924,"about_ca_system_score_gemma":0.0004120599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01277323,"about_ca_topic_score_gemma":0.008730615,"domain_scores_codex":[0.9995273,0.0001995868,0.00005772309,0.00005593562,0.00007115591,0.00008835697],"domain_scores_gemma":[0.99873,0.0004429338,0.000471424,0.0001182251,0.0001530029,0.00008438862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000150729,0.0001068977,0.9706039,0.0001110032,0.0003061847,0.0005093733,0.00169897,0.007161948,0.0004951025,0.001908174,0.0007081254,0.01623956],"study_design_scores_gemma":[0.00001036756,0.0001129421,0.9872636,0.00005442233,0.0000805102,0.0002283077,0.004357415,0.002770908,0.0004849865,0.0004230938,0.004194193,0.00001933155],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982317,0.0001758457,0.0003119996,0.00003671518,0.000001415215,0.00001096101,0.000475586,0.000001803206,0.0007539321],"genre_scores_gemma":[0.9977488,0.0003686604,0.0004047213,0.00001475434,0.000002436256,0.00001569623,0.001191882,0.000002823975,0.0002504298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01277323,"threshold_uncertainty_score":0.02539772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02287925947079707,"score_gpt":0.3643211571499494,"score_spread":0.3414418976791523,"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."}}