La cooperació penal de la UE amb tercers estats a través dels acords internacionals : una valoració post Lisboa
Bibliographic record
Abstract
Aquesta col•lecció recull una selecció d'investigacions dutes a terme per estudiants del Màster Universitari en Integració Europea.Previ a la seva publicació, aquests treballs han estat tutoritzats per professors amb grau de doctor de diverses especialitats i han estat avaluats per un tribunal compost per tres docents distints del tutor.Les llengües de treball son castellà, català, anglès i francès Esta colección recoge una selección de investigaciones realizadas por estudiantes del Máster Universitario en Integración Europea.Previo a su publicación, los trabajos de investigación han sido tutorizados por profesores con grado doctor de diversas especialidades y han sido evaluados por un un tribunal compuesto por tres docentes distintos del tutor.Les lenguas de trabajo son catalán, castellano, inglés y francés This collection includes a selection of research by students of Master in European Integration.Prior to publication, the research papers have been tutored by teachers of with various specialties doctor degree and have been assessed by a commission composed of three different teachers tutor.Working languages: Catalan, Spanish, English and French Cette collection comprend une sélection de recherches par des étudiants de Master en intégration européenne.Avant la publication, les travaux de recherche ont été encadrés par des enseignants docteurs de diverses spécialités et après ont été évaluées par un tribunal composé de trois professeurs différents du tuteur.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.025 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".