Éditorial du numéro spécial "Les ontologies pour les EIAH"
Bibliographic record
Abstract
L'ingénierie ontologique est devenue depuis peu une composante incontournable des sciences cognitives. Dans un tel contexte, la communauté EIAH dont l'objet final est le partage et la transmission de la connaissance ne pouvait être en reste. Ainsi, l'ontologie et l'ingénierie ontologique sont des termes qui commencent à apparaître régulièrement dans les communications scientifiques de notre communauté [Crampes00] [RanwezCrampes01] [Psyché03] [Hibou03]. L'intérêt est croissant chez les chercheurs au niveau international comme en témoignent la tenue régulière de workshops ou tutorials sur le sujet dans les grandes conférences du domaine (ITS, AIED) et la sortie d'un numéro thématique "Ontologies and the Semantic Web for E-learning" de la revue Journal of Educational Technology and Society (2004, Vol. 7, Issue 4). Ce numéro spécial de la revue STICEF a pour but de faire un point sur cette nouvelle orientation dans la recherche et les pratiques des EIAH. (http://sticef.univ-lemans.fr/num/vol2004/sticef_2004_edito_special.htm)
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.024 | 0.012 |
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".