Reviewer Acknowledgements for Journal of Mathematics Research, Vol. 8, No. 1
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p><em>Journal of Mathematics Research</em> 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 is greatly appreciated.</p><p>Many authors, regardless of whether <em>Journal of Mathematics Research</em> publishes their work, appreciate the helpful feedback provided by the reviewers.</p><p><strong>Reviewers for Volume 8, Number 1</strong></p><p><strong> </strong></p><p>Alberto Simoes</p><p>Antonio Boccuto</p><p>Arman Aghili</p><p>Chung-Chuan Chen</p><p>Enrico Jabara</p><p>Kuldeep Narain Mathur</p><p>Luca Di Persio</p><p>Marek Brabec</p><p>Maria Alessandra Ragusa</p><p>Olivier Heubo-Kwegna</p><p>Ömür DEVECİ</p><p>Peng Zhang</p><p>Philip Philipoff</p><p>Prof. Sanjib Kumar Datta</p><p>R. Roopkumar</p><p>Rosalio G. Artes</p><p>Rovshan Bandaliyev</p><p>Saima Anis</p><p>Selcuk Koyuncu</p><p>Sergiy Koshkin</p><p>Vishnu Narayan Mishra</p><p>Waleed Al-Rawashdeh</p><p>Youssef El-Khatib</p><p>Zhongming Wang</p><p><strong> </strong></p><p>Sophia Wang</p><p>On behalf of,</p><p>The Editorial Board of <em>Journal of Mathematics Research</em></p><p>Canadian Center of Science and Education</p>
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.
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 | 0.103 | 0.533 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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 it