Bibliographic record
Abstract
L'article s'attaque au déficit diachronique en terminologie. La notion d'évolution est appliquée d'abord au micro-niveau, celui du terme, où il convient de distinguer l'évolution du signifiant et celle du signifié. Deux phénomènes relatifs à l'évolution formelle - l'expansion et la réduction - sont présentés. Au macro-niveau, celui d'une terminologie entière, une définition de l'évolution est proposée à partir d'un modèle conçu pour représenter les ensembles diachroniques des termes constituant une terminologie. Dans cette perspective, les lemmes d'un dictionnaire informatique (éditions 1970 et 1985) sont soumis à des analyses structurales diachroniques. Ces analyses montrent que l'importance des lemmes de l'édition de 1970 qui ne se retrouvent pas dans l'édition de 1985 est réduite et que leur structure est complexe. Les analyses révèlent aussi que les lemmes susceptibles de refléter le phénomène de la réduction sont rarissimes.
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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".