Enquête sur les Consultations des Définitions dans les Dictionnaires Français-Chinois par les Apprenants Chinois: Problèmes et Contre-Mesures
Bibliographic record
Abstract
D’apres l’enquete sur l’usage des dictionnaires francais-chinois par les apprenants chinois, les definitions du mot-entree, a defaut de mettre en evidence les caracteristiques du concept d’apprentissage au niveau de la macrostructure et de la microstructure dans les dictionnaires francais-chinois, ne sont pas satisfaisantes. Elles ne repondent pas aux besoins ni aux habitudes de consommation des lecteurs. Pour ameliorer la definition dans les dictionnaires francais-chinois destines aux apprenants chinois, l’auteur donne des conseils concernant le renforcement des caracteristiques d’apprentissage, l’adaptation a la structure et les besoins en connaissances des apprenants.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.042 | 0.024 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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; both teacher heads agree on what is shown here.
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".