Bibliographic record
Abstract
Les internationalismes de langues de spécialité, en particulier ceux d'origine gréco-latine, peuvent certes être une aide pour le traducteur technique; mais ce dernier se doit toutefois d'éviter les erreurs que peut entraîner l'utilisation irréfléchie de termes étrangers, ce que quelques exemples mettent en lumière. La suite de l'article, s'appuyant sur un modèle didactique concret, explique comment intégrer, dans le cadre d'un cursus pour traducteurs techniques, une introduction systématique aux formants internationaux. L'étude systématique des formants internationaux aide l'étudiant à comprendre des termes jusque-là inconnus tout en représentant un support important à la mémorisation des terminologies. En outre, la comparaison critique entre termes de différentes langues lui montre que l'identité de la forme ne permet pas de conclure sans réserve à l'identité du contenu.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".