{"id":"W2897372017","doi":"10.26481/dis.20180926ah","title":"Counting for EU enlargement?","year":2018,"lang":"en","type":"dissertation","venue":"","topic":"European Union Policy and Governance","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Council on Foreign Relations","funders":"","keywords":"Census; Resizing; Member states; Geography; Population; Political science; Politics; Eu countries; Variation (astronomy); Order (exchange); Regional science; European union; Demography; Law; International trade; Business; Sociology","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":[0.02553038,0.0005499311,0.0008051643,0.00241716,0.005357507,0.01047559,0.002070598,0.002115598,0.01367763],"category_scores_gemma":[0.07789648,0.0003616478,0.0005613083,0.005785236,0.01311522,0.02182022,0.007795772,0.00430932,0.001305304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004695807,"about_ca_system_score_gemma":0.006671301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007275974,"about_ca_topic_score_gemma":0.006602604,"domain_scores_codex":[0.9773527,0.01426123,0.001049757,0.002832996,0.002833496,0.001669792],"domain_scores_gemma":[0.9682025,0.01767897,0.002639588,0.005113902,0.004756301,0.001608731],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004879008,0.00002906573,0.005176213,0.000222769,0.00001623027,0.00009689363,0.02650519,0.0002255136,0.0001092157,0.8595951,0.04097481,0.06700012],"study_design_scores_gemma":[0.00001964547,0.00005323529,0.01416805,0.001814615,0.00002392567,0.0001948134,0.07454998,0.000815601,0.0007158234,0.3210676,0.5865167,0.0000599952],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1324885,0.02420482,0.03210136,0.2717492,0.00783954,0.0002772702,0.001119356,0.0004955398,0.5297244],"genre_scores_gemma":[0.9288319,0.00593865,0.01301547,0.02252123,0.001558302,0.0004654383,0.0007519703,0.0003723102,0.02654469],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.02553038,"threshold_uncertainty_score":0.1350192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03143514503231093,"score_gpt":0.3626663410012976,"score_spread":0.3312311959689867,"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."}}