Bibliographic record
Abstract
This study analyzes final devoicing in Russian using quantitative methods. It is well-known that, in Russian voiceless consonants and voiced consonants that undergo voiceless assimilation (e.g., /pod/ vs. /pot/) are not acoustically identical in terms of the preceding vowel length, indicating the occurrence of incomplete neutralization. However, previous studies have relied on small-scale, tightly controlled manual data. This study attempts a corpus-based linguistic analysis of vowel length, one of the main cues to incomplete neutralization, by using a large speech corpus(RUSLAN) and the forced aligner tool Montreal Forced Aligner(MFA). The results show that, for all voiced-voiceless pairs, the vowel preceding the voiceless-assimilated voiced consonant tends to be longer. However, exceptions were observed in certain consonant pairs, which deviate from the initial hypothesis. These findings suggest the potential for phonetic research using large, naturally occurring speech data.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".