{"id":"W7133051384","doi":"","title":"Mutual recognition in the third pillar of EU law: a shaky cornerstone","year":2007,"lang":"","type":"dissertation","venue":"TSpace","topic":"European Criminal Justice and Data Protection","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Heritage; University of Toronto","funders":"University of Toronto","keywords":"Mutual recognition; Cornerstone; Human rights; Pillar; Legislature; European union; Work (physics)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003765687,0.0003383438,0.0004126555,0.0002537413,0.0005629737,0.000117565,0.0006291653,0.0004659148,0.0003340268],"category_scores_gemma":[0.0006688737,0.0002950833,0.0001679104,0.001062286,0.000480525,0.0003323786,0.00004251804,0.0008911651,0.0005049328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001112586,"about_ca_system_score_gemma":0.0002111022,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03232991,"about_ca_topic_score_gemma":0.03460492,"domain_scores_codex":[0.9962603,0.0009733426,0.0006866065,0.0005357864,0.001027671,0.0005162208],"domain_scores_gemma":[0.9978768,0.0005498641,0.0007419145,0.0003968865,0.0003411405,0.00009335915],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.001924777,0.0006847004,0.00003376376,0.001218306,0.00007298115,0.0001369733,0.9374195,0.00001391811,0.004254284,0.0181334,0.002378462,0.03372898],"study_design_scores_gemma":[0.0005331538,0.0006592485,0.0008804035,0.0008103151,0.0004841687,0.000009707257,0.9646019,0.00005310172,0.002120595,0.0005884345,0.02876597,0.0004930026],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6158485,0.0007603739,0.0002173404,0.0004785836,0.001063748,0.001177974,0.00003828022,0.00004007242,0.3803751],"genre_scores_gemma":[0.9890301,0.003213759,0.0002804447,0.001055137,0.0008360014,0.00003648854,0.0009572167,0.00004944557,0.0045414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3758337,"threshold_uncertainty_score":0.9999501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08320152446164587,"score_gpt":0.4151365291766477,"score_spread":0.3319350047150018,"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."}}