Bibliographic record
Abstract
La quantite et la qualite des etudes sur un tel sujet dependent grandement de l`accessibilite de ses references. Le 《Dictionnaire Coreen-Francais(1880)》(DCF) publie par des missionnaires de la Societe des missions etrangeres de Paris etait estime comme le premier dictionnaire bilingue systematique concernant la langue coreenne, mais des chercheurs coreens sont en train d`oublier son importance, a cause de la langue francaise qu`ils ne comprennent plus, et du material d`imprimerie en papier qui empeche la facilite de recherche. Nous avons propose de construire une base des connaissances a partir de DCF, afin de surmonter ce type d``obstacles. A la suite de cette etude precedente, ce present travail propose la construction d`un autre dictionnaire bilingue, 《Dictionnaire Coreen-Anglais (1911)(DCA)》, publie une trentaine d`annees plus tard par un missionnaire canadien James Scarth Gale, qui a precise l`influence du DCF sur son DCA dans son ouvrage, Or, des traces du DCA sont encore trouvees dans des dictionnaires contemporains. Nous esperons que DCA sert a specifier les caracteristiques du DCF. L`objectif final de nos etudes consiste a construire une base des connaissances integre, qui vise a augmenter l``interchangeabilite des informations linguistiques entre DCF, DCA, et d`autres dictionnaires qui seront ulterieurement construits. D`abord, nous examinons les etudes preexistantes qui concernent DCF et DCA dans la deuxieme section. La troisieme est consacree a analyser la micro-structure de DCA. Apres avoir applique les definitions du LEXml aux divers types d`informations linguistiques de DCA, nous dressons les regles generales et specifiques determinant la structure des deux dictionnaires, dans la quatrieme section. Finalement, la derniere section presente les necessites de nos recherches du present et celles du futur.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 0.003 |
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".