{"id":"W6982280053","doi":"","title":"How big is the 'German locomotive'? A perspective from Central and Eastern European countries' unemployment rates
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\\n","year":2011,"lang":"en","type":"book","venue":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","topic":"Unemployment and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Junta de Castilla y León; Generalitat Valenciana; Trent University; Nottingham Trent University","keywords":"Unemployment; Business cycle; German; Post communist; Sample (material); Perspective (graphical); Transition (genetics); Convergence (economics); German economy","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00126484,0.0005613721,0.001316933,0.0009414484,0.001208513,0.0000752942,0.002976712,0.000544928,0.001575452],"category_scores_gemma":[0.00003875626,0.000663095,0.0006700722,0.0004674592,0.003762114,0.0005209887,0.002091962,0.001503726,0.0001509154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007118684,"about_ca_system_score_gemma":0.0004175402,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0349752,"about_ca_topic_score_gemma":0.01874544,"domain_scores_codex":[0.9968269,0.0003917105,0.0004023808,0.001127242,0.0004003113,0.0008514838],"domain_scores_gemma":[0.9961362,0.0004425477,0.001256439,0.001215948,0.0005891878,0.0003596484],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.008005727,0.003415364,0.1228714,0.001690549,0.01300909,0.0009605105,0.5447274,0.0003110658,0.00007281338,0.1117899,0.1826019,0.01054429],"study_design_scores_gemma":[0.008970672,0.001494246,0.05372543,0.001074064,0.0009082292,0.00001290789,0.1819572,0.002734712,0.00003155941,0.01938473,0.7277973,0.001909037],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.5659045,0.004956301,0.003089807,0.02940076,0.0005561699,0.002707856,0.01046437,0.0001392159,0.382781],"genre_scores_gemma":[0.4727686,0.009393563,0.0002704552,0.00009186457,0.0002132676,4.934024e-8,0.0003084092,0.00007908092,0.5168747],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5451953,"threshold_uncertainty_score":0.9995821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06083239129955084,"score_gpt":0.2240483420178233,"score_spread":0.1632159507182724,"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."}}