{"id":"W7096125747","doi":"","title":"Michio Suzuki","year":2009,"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":"Inequality; Consumption (sociology); Confidentiality; Economic inequality; Distribution (mathematics); Offset (computer science); Wage","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005956191,0.0004857449,0.0003797234,0.001039335,0.002085597,0.002386964,0.0009695745,0.001072085,0.2103672],"category_scores_gemma":[0.002008987,0.0002462883,0.0002872356,0.0006919542,0.0005592334,0.001536535,0.001995919,0.001685158,0.1053171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001591237,"about_ca_system_score_gemma":0.003106408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01039645,"about_ca_topic_score_gemma":0.02008449,"domain_scores_codex":[0.9993472,0.00005852283,0.00003101417,0.0001954461,0.0002408227,0.0001271596],"domain_scores_gemma":[0.9990335,0.0001032095,0.00004757549,0.00007982584,0.0003820027,0.0003539183],"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":[0.0001301263,0.00006204909,0.003523883,0.0003527993,0.00002003119,0.001058597,0.00063154,0.0002600258,0.001844108,0.03659555,0.6393608,0.3161605],"study_design_scores_gemma":[0.000004799837,0.000007013075,0.000794273,0.00005639769,0.000006234643,0.0003713163,0.000158221,0.00009275592,0.0003371013,0.001776336,0.9963871,0.000008473708],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.008316633,0.01736534,0.009620654,0.04987461,0.01245497,0.00011913,0.001958103,0.001265632,0.8990248],"genre_scores_gemma":[0.04264736,0.01119589,0.005238013,0.007757322,0.00131105,0.00007484986,0.001082507,0.0003564671,0.9303366],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7896328,"threshold_uncertainty_score":0.7037485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03664808073726546,"score_gpt":0.3359790744125944,"score_spread":0.299330993675329,"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."}}