{"id":"W4313827112","doi":"10.1108/s1049-258520230000030012","title":"Index","year":2023,"lang":"en","type":"paratext","venue":"","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inequality; Economic inequality; Index (typography); Mathematics; Gini coefficient; Econometrics; Statistics; Income inequality metrics; Economics; Demography; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001435869,0.001841593,0.001490432,0.005819218,0.002141865,0.01094164,0.002707052,0.002738466,0.8179134],"category_scores_gemma":[0.007384826,0.000645369,0.001303338,0.009186131,0.0007111508,0.007133773,0.004009347,0.00218768,0.8354132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002374236,"about_ca_system_score_gemma":0.004265463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008061275,"about_ca_topic_score_gemma":0.007772637,"domain_scores_codex":[0.998125,0.0001652896,0.0001777257,0.0003842602,0.0009342823,0.0002133333],"domain_scores_gemma":[0.9962307,0.0002884861,0.0001461974,0.0005356464,0.002197842,0.0006011623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001192225,0.00001144287,0.0001308452,0.0001556888,0.000002568934,0.00001505097,0.00002131163,0.00002141658,0.00006938243,0.001910116,0.9399144,0.05773586],"study_design_scores_gemma":[0.000002773797,0.000005292664,0.0002523339,0.00009000648,0.0000014487,0.00002496329,0.00003197205,0.00001975768,0.00003396341,0.0006848821,0.998848,0.000004579157],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0005155185,0.004012675,0.001771297,0.005733861,0.01456634,0.0003795242,0.05627757,0.00436627,0.9123769],"genre_scores_gemma":[0.001620703,0.003146172,0.001578278,0.002262285,0.002040131,0.00028284,0.04361697,0.001495909,0.9439567],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8179134,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06984579003706194,"score_gpt":0.3745020956305093,"score_spread":0.3046563055934474,"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."}}