Bibliographic record
Abstract
SUMMARY The MACS (Multilingual access to subjects) project is one of the many projects that are currently exploring solutions to multilingual subject access to online catalogs. Its strategy is to develop a Web-based link and search interface through which equivalents between three Subject Heading Languages–SWD/RSWK (Schlagwortnormdatei/Regeln für den Schlagwortkatalog) for German, RAMEAU (Répertoire d'Autorité-Matière Encyclopédique et Alphabétique Unifié) for French, and LCSH (Library of Congress Subject Headings) for English–can be created and maintained, and by which users can access online databases in the language of their choice. Factors that have led to this approach will be examined and the MACS linking strategy will be explained. The trend to using mapping or linking strategies between different controlled vocabularies to create multilingual access challenges the traditional view of the multilingual thesaurus.
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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.012 | 0.020 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".