{"id":"W3005106710","doi":"","title":"Informal employment in Kazakhstan: a blessing in disguise?","year":2018,"lang":"en","type":"article","venue":"London School of Economics and Political Science Research Online (London School of Economics and Political Science)","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Earnings; Blessing; Matching (statistics); Informal sector; Quarter (Canadian coin); Economics; Labour economics; Demographic economics; Economic growth; Accounting; Geography","routes":{"ca_aff":false,"ca_fund":true,"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":[0.001592177,0.0002456551,0.0003793068,0.001752745,0.002400023,0.003054725,0.0005546472,0.0006912558,0.002450906],"category_scores_gemma":[0.002934813,0.0001226425,0.0002214897,0.003858802,0.003545081,0.002824305,0.002352397,0.001049667,0.0003648154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001268825,"about_ca_system_score_gemma":0.001786469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02983341,"about_ca_topic_score_gemma":0.04979544,"domain_scores_codex":[0.9993373,0.0002897436,0.00005238856,0.00007405819,0.0001019228,0.0001445186],"domain_scores_gemma":[0.9989572,0.0003312983,0.0002880286,0.0001187371,0.0001734607,0.0001312591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006299743,0.0001535894,0.4919367,0.0009303995,0.0002129301,0.00193205,0.05497053,0.00205732,0.001978815,0.1503893,0.03100805,0.2638004],"study_design_scores_gemma":[0.00003061949,0.000203602,0.7132674,0.001540576,0.0001391313,0.001447131,0.1307691,0.001785281,0.0004674951,0.06833223,0.08192266,0.00009470158],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.891414,0.02176358,0.003157849,0.06734305,0.001203219,0.00001562259,0.0006552483,0.0000560401,0.01439132],"genre_scores_gemma":[0.9937314,0.00302216,0.0005377642,0.001616537,0.0004232212,0.000004258213,0.0001340719,0.00000750654,0.0005230661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02983341,"threshold_uncertainty_score":0.0593195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09626970652418518,"score_gpt":0.453725051006776,"score_spread":0.3574553444825908,"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."}}