Comparative Analysis of Melodic Variation of Concession Clauses with Two or More Syntagms in English and Azerbaijani
Why this work is in the frame
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Bibliographic record
Abstract
The article is devoted to the problem of comparative analysis of melodic variation of concession clauses with two or more syntagms in English and Azerbaijani. The research has been done on the basis of comparative-typological and experimental-phonetic methods, as both of the languages belong to different language families and they have different language systems. A lot of sentences from both languages have been chosen to carry out the experiment. A great attention has been paid to the sentences with two-syntagms and three-syntagms depending on the purpose of the research. After getting the results of experiment, the part of material belonging to English has been compared with the part that belongs to Azerbaijani. For this purpose PRAAT computer program has been used.
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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 | 0.084 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it