{"id":"W7097767317","doi":"","title":"Chapter 1 MAGNITUDE OF INEQUALITIES","year":2011,"lang":"en","type":"article","venue":"","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Latin Americans; Quarter (Canadian coin); Per capita income; Inequality; Income distribution; Population; Economic inequality; Distribution (mathematics); Per capita","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":[0.001316693,0.0004951839,0.0004061922,0.002667845,0.001834302,0.005866226,0.0008419488,0.001249476,0.05780101],"category_scores_gemma":[0.005313813,0.0002387558,0.0003308973,0.004078636,0.00177927,0.004084567,0.002745261,0.002363269,0.003144133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002845281,"about_ca_system_score_gemma":0.003673984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008217758,"about_ca_topic_score_gemma":0.01061996,"domain_scores_codex":[0.9985319,0.0003232757,0.00004860532,0.0001968255,0.0006128093,0.0002865698],"domain_scores_gemma":[0.9982488,0.0007498494,0.0002374503,0.0001123464,0.0004407446,0.0002108493],"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":[0.0000278338,0.00003820674,0.009770373,0.0006719918,0.00002711574,0.00008763009,0.001987874,0.0003832502,0.0002091927,0.7456757,0.1260567,0.115064],"study_design_scores_gemma":[0.000008347783,0.00004844284,0.02618888,0.004284854,0.00003123332,0.0003363674,0.006632623,0.0004554798,0.0002648033,0.245216,0.7165086,0.00002442032],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01565843,0.07318403,0.004047056,0.09032445,0.003777505,0.0001669416,0.004501264,0.00009410054,0.8082462],"genre_scores_gemma":[0.672045,0.1328731,0.006281271,0.01460094,0.01317631,0.0004239486,0.004387393,0.0001688733,0.1560432],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05780101,"threshold_uncertainty_score":0.1933636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1259669927294726,"score_gpt":0.3270902409864935,"score_spread":0.2011232482570209,"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."}}