Overlay Journals, Overlay Reviews: Has Their Time Finally Come?
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
MODERATOR: Heather R Staines Independent Consultant Trumbull, Connecticut SPEAKERS: Hannah Drury Product Manager eLife/Sciety Peterborough, United Kingdom Samantha Hindle Content Manager bioRxiv and medRxiv Cofounder PREreview Stefano M Bertozzi Dean Emeritus and Professor of Health Policy and Management UC Berkeley School of Public Health Gunther Eysenbach CEO and Executive Editor JMIR Publications Toronto, Ontario, Canada REPORTER: Tony Alves Hopedale, Massachusetts The session “Overlay Journals, Overlay Reviews: Has Their Time Finally Come?” was held virtually on May 4, 2021. Moderated by Heather Staines, Senior Consultant at Delta Think, the session featured presentations by Stefano M Bertozzi, Dean Emeritus and Professor of Public Health Policy and Management at UC Berkeley; Gunther Eysenbach, CEO and Executive Editor, JMIR Publications; Samantha Hindle, Content Manager of bioRxiv and medRxiv and Co-founder of PREreview; and Hannah Drury, Product Manager of Sciety at eLife. COVID-19 has accelerated the use of preprints, and researchers and media are increasingly turning to preprint servers to get an early glimpse at new studies. Preprint servers have come under increased scrutiny, and many have risen to the challenge by implementing various forms of peer review. Another interesting and related phenomenon is the increase in “overlay journals,” which use “overlay reviews” to help validate the science in preprints, thus increasing trust and transparency in preprints. If you are unfamiliar with the concept of overlay journals, they are a type of online, open access compilation of preprints, public domain publications, and already-published open access articles. Sometimes the compilations are thematic, addressing specific topics, and […]
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 | 0.028 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.008 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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