Bibliographic record
Abstract
Review of European Studies wishes to acknowledge the following individuals for their assistance with peer review of manuscripts for this issue. Their help and contributions in maintaining the quality of the journal are greatly appreciated.
 
 Review of European Studies is recruiting reviewers for the journal. If you are interested in becoming a reviewer, we welcome you to join us. Please find the application form and details at http://recruitment.ccsenet.org and e-mail the completed application form to res@ccsenet.org.
 
 Reviewers for Volume 11, Number 3
 
 Alejandra Moreno Alvarez, Universidad de Oviedo, Spain
 
 Ali S.M. Al-Issa, Sultan Qaboos University, Oman
 
 Ani Derderian, WSU, USA
 
 Anna Grana, University of Palermo, Italy
 
 Annalisa Pavan, University of Padova, ITALY
 
 Edwards, Beverly L, Fayetteville State University Department of Social Work, United States
 
 Eugenia Panitsides, University of Macedonia, Greece
 
 Florin Ionita, The Bucharest Academy of Economic Studies, Romania
 
 Gabriela Gruber, Lucian Blaga University of Sibiu, Romania
 
 Gülce Başer, Boğaziçi University, Tukey
 
 Hiranya Lahiri, M.U.C Women’s College, Burdwan, India
 
 Ifigeneia Vamvakidou, University of Western Macedonia, Greece
 
 Ioan-Gheorghe Rotaru, ‘Timotheus’ Brethren Theological Institute of Bucharest, Romania
 
 Johnnie Woodard, Independent Scholar, USA
 
 Karen Ferreira-Meyers, University of Swaziland, Swaziland
 
 Lena Arampatzidou, Aristotle University of Thessaloniki, Greece
 
 Maria Pescaru, University of Pitești, ROMANIA
 
 Meenal Tula, University of Hyderabad, India
 
 Pri Priyono, universities PGRI adi buana, Indonesia
 
 Ronald James Scott, Leading-Edge Research Institute, USA
 
 Sara Núñez Izquierdo, University of Salamanca, Spain
 
 Smita M. Patil, School of Gender and Development Studies, India
 
 Szabolcs Blazsek, Universidad Francisco Marroquin, Guatemala
 
 Tryfon Korontzis, Hellenic National School of Local Government , Greece
 
 Vicenta Gisbert, Universidad de La Laguna, Spain
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.203 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".