Bibliographic record
Abstract
The cover image was created by a participant during the 2024 ESJP conference held at Chalmers University of Technology, Gothenburg Sweden, and online, during August 12-15, 2024. The painting was left among creations possible for the editors to include in this special issue. While we do not know the creator’s original interpretation, the editors think the image captures the conference theme of Another university is possible! Maybe as a move from something quite monolithic and mostly gray to something more multidimensional and colorful? After the issue had been published the creator behind the cover image became known to the editors, and was no other than Katerina Pia Günter, who has two other arts-related contributions in this special issue! Katerina: The creator of the front matter image is very pleased with the interpretation, haha! And honoured it is serving a purpose! Thank you so much for all the work you poured into this Special issue!!! Corey: Perhaps I should have guessed… All we did was set up a space, but you took it and ran!!! So much of the issue is your work! Thank you so much for sharing so much Katerina <3 (Communication between artist Katerina Pia Günter and editor Corin (Corey) Bowen on 2025-06-29)
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 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 | 0.000 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.889 | 0.686 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".