{"id":"W1581253759","doi":"10.15353/rea.v2i1.1490","title":"Labour Market Dynamics in Greek Regions: a Bayesian Markov Chain Approach Using Proportions Data","year":2010,"lang":"en","type":"article","venue":"Review of Economic Analysis","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Unemployment; Markov chain Monte Carlo; Bayesian probability; Economics; Markov chain; Econometrics; Convergence (economics); Distribution (mathematics); Statistics; Mathematics; Macroeconomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.003596986,0.0003788578,0.00123018,0.001945124,0.0005454386,0.001862483,0.001231162,0.001218269,0.003113476],"category_scores_gemma":[0.01157648,0.0006713168,0.001261338,0.001644605,0.0009197163,0.001970208,0.001414787,0.001319488,0.0004320254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001216333,"about_ca_system_score_gemma":0.0009780457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03991004,"about_ca_topic_score_gemma":0.02614561,"domain_scores_codex":[0.99882,0.0007106166,0.00005713672,0.0002202885,0.00009156896,0.0001003763],"domain_scores_gemma":[0.9953831,0.003679466,0.0004566525,0.0002053817,0.0001851699,0.00009023857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001789388,0.0001140622,0.04839763,0.0001468223,0.0002395057,0.0005345894,0.001045208,0.7961335,0.0005320349,0.1203872,0.001227323,0.0310632],"study_design_scores_gemma":[0.00001913056,0.0000210445,0.006592603,0.00005089253,0.00003356085,0.00004452259,0.0001712572,0.9518003,0.0001114965,0.04002666,0.001101491,0.00002708453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6912245,0.001939592,0.297584,0.00101135,0.00004473512,0.00019984,0.001730876,0.0001490627,0.006116111],"genre_scores_gemma":[0.961563,0.001728653,0.03191229,0.00008348731,0.0000583604,0.0001691914,0.001783787,0.00004096342,0.002660388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03991004,"threshold_uncertainty_score":0.07935548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04246545170780552,"score_gpt":0.2834048206425657,"score_spread":0.2409393689347601,"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."}}