Bibliographic record
Abstract
This session described the 2015 pilot project and ongoing cooperation between the International ISSN Centre based in Paris and ProQuest to identify active titles without ISSN. The project is using Ulrich’s periodicals database as the initial resource. Under the supervision of the International Centre, national ISSN centers determine whether the ISSN is simply missing or has never been assigned. The outcome of the project will be a benefit to librarians, publishers, and vendors as more titles will have ISSN registered with the national and international ISSN centers and in Ulrich’s Periodical Database. This will improve the electronic loading and matching of titles. Gaëlle Béquet, director of the International ISSN Centre, and Laurie Kaplan of ProQuest discussed how the project came to be, the pilot work and refinements to the process, and the ongoing work and schedule for going forward. The audience was encouraged to ask questions and help determine the best way to encourage all interested parties to use the ISSN as an identifier whenever possible.
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 | 0.119 | 0.156 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.018 | 0.025 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 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 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".