{"id":"W4230290890","doi":"10.31235/osf.io/78yhf","title":"Dynamics of Asset Poverty in South Korea","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Korean Urban and Social Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; The Wilson Centre","funders":"","keywords":"Poverty; Asset (computer security); Diversification (marketing strategy); Panel data; Economics; Welfare; Portfolio; Demographic economics; Development economics; Economic growth; Business; Finance; Econometrics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000418573,0.0001003811,0.0001772913,0.0005782463,0.0003656237,0.0007873758,0.0002389662,0.0002186349,0.00206153],"category_scores_gemma":[0.001556278,0.0001760401,0.0001790999,0.0008782148,0.0003586451,0.0008856484,0.001303196,0.0004906377,0.0001157713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007491369,"about_ca_system_score_gemma":0.0004569937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01763815,"about_ca_topic_score_gemma":0.01746622,"domain_scores_codex":[0.9998287,0.00004806874,0.000009651099,0.00003110681,0.00001829355,0.00006415302],"domain_scores_gemma":[0.999443,0.0001045672,0.0002265158,0.00004187134,0.0000905592,0.0000935479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000198657,0.0001055078,0.95821,0.00004929234,0.00009056881,0.0008353894,0.002745074,0.007892272,0.0009782327,0.008259084,0.002250896,0.01838504],"study_design_scores_gemma":[0.00001080172,0.00007060138,0.9659642,0.00004576942,0.00002982622,0.0003398425,0.008345361,0.01683374,0.0002815396,0.005512173,0.002537549,0.00002844865],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982532,0.00006811254,0.0001893972,0.0003467254,0.000001306231,0.000004727749,0.0003663834,0.000003273067,0.0007669808],"genre_scores_gemma":[0.9995341,0.00006345564,0.00005169043,0.00002189604,6.018589e-7,0.000003903091,0.0001462148,0.00000108054,0.0001771129],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01763815,"threshold_uncertainty_score":0.03507096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0206157148128582,"score_gpt":0.2480142678255474,"score_spread":0.2273985530126892,"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."}}