{"id":"W7098216775","doi":"","title":"The Ins and Outs of Poverty in Advanced Economies: Government Policy and Poverty Dynamics in","year":2006,"lang":"en","type":"article","venue":"","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Poverty; Chronic poverty; Government (linguistics); Public policy; Culture of poverty; Basic needs","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001007882,0.0000679233,0.00009853901,0.00001465912,0.0000189264,0.000007744435,0.00006075144,0.00008450825,0.000001550701],"category_scores_gemma":[0.00011864,0.00004439093,0.00001397397,0.00003839057,0.0001173102,0.000001804367,0.00009356385,0.00004156018,1.794121e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005072506,"about_ca_system_score_gemma":0.00002698898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007560064,"about_ca_topic_score_gemma":0.01334266,"domain_scores_codex":[0.9995071,0.0000168483,0.0001561362,0.0001427755,0.00004792887,0.0001291735],"domain_scores_gemma":[0.999785,0.00004320831,0.00003818967,0.0001074643,0.000005613409,0.00002053352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005399926,0.0002812211,0.6202972,0.00007999419,0.00004715213,0.000005925828,0.0001565873,0.00007666487,0.03689148,0.02010761,0.004073326,0.3174429],"study_design_scores_gemma":[0.003972007,0.0006843585,0.8909876,0.00004945602,0.000007704724,0.00001191466,0.00275835,0.004269191,0.01951555,0.005329232,0.07199147,0.0004231143],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896516,0.000541763,0.00006327751,0.001314549,0.00002166281,0.00006276555,0.0000200903,0.00000280776,0.008321477],"genre_scores_gemma":[0.9974496,0.0005625356,0.0005145906,0.0003506205,0.00001930248,0.000004615645,0.000005737084,0.000003794623,0.001089141],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3170198,"threshold_uncertainty_score":0.744552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003831441693398207,"score_gpt":0.2294245938843939,"score_spread":0.2255931521909957,"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."}}