Problems of Creation of Etymological Dictionary of Suffixes of Ukrainian Language
Bibliographic record
Abstract
Etymology as a study connected with reconstruction of the primary (veritable) meaning of a word was originated in ancient Greek linguistics according to well known discussion about the character of names. But as a scientific method and separate linguistic branch it has been formed only after the appearing of comparative-historical linguistics which achieved great results during less than two centuries of its development.The main acquisition of it was the creation of etymological national dictionaries, related or prehistoric (for example, of primitive Slavonic language) the first of which was in Europe "Етимологічний словник романських мов" (1853) Ф.Діца and in Slavic studies - "Етимологічний словник слов'янських мов" (1886) Ф.МІклошнча which was published in German language. "Етимологічний словник української мови" in two volumes Я.Рудницький published in Winnipeg during 1962-1982 and then came similar dictionary under the editorship of О.С.Мельничук in seven volumes (as for today 5 volumes are published).
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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".