Bibliographic record
Abstract
The article presents an analysis of 140 random lexemes of Greek and Latin origin excerpted from Słownik kieszonkowy polsko-rosyjski i rosyjsko-polski [Pocket Polish-Russian and Russian-Polish Dictionary] edited by I. Mitronova, G. Sinicyna and G. Lipkes. The corpus is, according to lexicographers and linguists, an effect of mutual influences of Polish and Russian languages. The opinions on origins of words differ among researchers, and the article attempts to verify the previously accepted judgements by M. Vasmer, W. Witkowski and Z. Rysiewicz, based on informations included in monographs by D. Moszyńska, H. Leeming, S. Kochman, and in historical dictionaries of both languages. With reference to almost 75% of the analysed material, the direction of loanword acquisition proposed by Vasmer, Witkowski and Rysiewicz has been confirmed. However, for about a quarter of the random sample of words, the accepted opinion is not confirmed by more recent historical dictionaries, nor by the lexical material provided in the monographs. The article proposes new results for the direction of loanword migration in this group of vocabulary.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".