{"id":"W1986374619","doi":"10.1007/s11205-009-9566-y","title":"“Healthy” Human Development Indices","year":2009,"lang":"en","type":"article","venue":"Social Indicators Research","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Human Development Index; Life expectancy; Ranking (information retrieval); Outlier; Rank correlation; Rank (graph theory); Human development (humanity); Demography; Quality of Life Research; Index (typography); Geography; Public health; Psychology; Statistics; Medicine; Economic growth; Economics; Mathematics; Sociology; Population; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.008015179,0.0001281362,0.0002307307,0.0005654592,0.00752923,0.0002043054,0.0007980738,0.0003273383,0.0007005865],"category_scores_gemma":[0.0003366228,0.0001281079,0.00007922504,0.001655748,0.0009004443,0.0002366446,0.00009744129,0.0007958888,0.0003505023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009419641,"about_ca_system_score_gemma":0.001642766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003067602,"about_ca_topic_score_gemma":0.002483746,"domain_scores_codex":[0.9944553,0.00133075,0.0003948497,0.0003594632,0.002246379,0.001213226],"domain_scores_gemma":[0.9989615,0.0001616997,0.0001237773,0.0001715091,0.0002173274,0.0003642],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005835464,0.0006386885,0.04510101,0.00003696518,0.00003937238,0.00001246697,0.2743083,4.916438e-8,0.0001177363,0.5114986,0.05029983,0.1178885],"study_design_scores_gemma":[0.0005173355,0.0002552427,0.2639159,0.000016932,0.00000382901,1.508592e-7,0.02103326,3.025526e-7,0.0004210152,0.01811292,0.6953976,0.0003255616],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7078023,0.00007849223,0.00000422204,0.004359762,0.0001269006,0.0003250712,0.000002716578,0.0001012554,0.2871993],"genre_scores_gemma":[0.9948348,0.00005015024,0.00006178658,0.000715551,0.001284734,0.00002705443,0.00001391627,0.00001188471,0.003000073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6450977,"threshold_uncertainty_score":0.9937629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1885662966877592,"score_gpt":0.5074126960675146,"score_spread":0.3188463993797553,"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."}}