{"id":"W1511675356","doi":"10.2139/ssrn.1578342","title":"Inequality, Polarization and Poverty in Nigeria","year":2010,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Australian Agency for International Development; International Development Research Centre; Government of Canada; United States Agency for International Development","keywords":"Poverty; Inequality; Polarization (electrochemistry); Development economics; Economic inequality; Geography; Political science; Economics; Socioeconomics; Economic growth; Mathematics; Chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0007869832,0.000127576,0.0002270009,0.001386711,0.003065851,0.002072494,0.0001745239,0.000517994,0.00258348],"category_scores_gemma":[0.001833401,0.0001445945,0.0001076577,0.001816471,0.002117963,0.001423737,0.001970516,0.0009953167,0.0001216524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001521498,"about_ca_system_score_gemma":0.001878681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01533563,"about_ca_topic_score_gemma":0.0338636,"domain_scores_codex":[0.99961,0.000154561,0.00002056298,0.00002136459,0.00005182941,0.0001416589],"domain_scores_gemma":[0.9990288,0.0004005117,0.0002336581,0.0000237674,0.0001010487,0.0002122691],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002901065,0.0003990913,0.8578713,0.00009467266,0.00003287244,0.0006394309,0.01243793,0.000592911,0.0003033554,0.09504434,0.001672488,0.0306215],"study_design_scores_gemma":[0.00001708848,0.0001273301,0.8773662,0.0003503024,0.0000428692,0.000619724,0.06419738,0.001905948,0.0002635651,0.04584598,0.009237354,0.00002638668],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9784038,0.001388226,0.00009422685,0.002362609,0.0000253142,0.000005497753,0.00006568797,9.651391e-7,0.01765371],"genre_scores_gemma":[0.9990916,0.0005209512,0.00002031016,0.00003014505,0.00000828277,0.000002996681,0.000009957674,3.408759e-7,0.0003153255],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01533563,"threshold_uncertainty_score":0.03049272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01323487020111642,"score_gpt":0.2973699435419104,"score_spread":0.284135073340794,"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."}}