Bibliographic record
Abstract
This study examines the acoustics of vowels from two Totonacan languages, Upper Necaxa Totonac (UNT) and Huehuetla Tepehua (HT). Both languages have five-vowel systems consisting of the qualities /aeiou/ as well as phonemic quantity distinctions (short, long), and lexical stress. In addition, UNT makes use of contrastive phonation on vowels, while HT vowels may be produced with allophonically non-modal phonation when adjacent to glottalic segments and glottal stops. Data from four speakers (two female and two male) of each language are reported. Acoustic measures are based on multiple repetitions of each vowel in a variety of lexical items, elicited within a frame sentence. Measurements are taken from stressed vowels surrounded by obstruents wherever possible. A variety of analyses are undertaken. Traditional visualizations of the vowel spaces of male and female speakers using normalized F1-F2 plots are combined with comparisons of dynamic formant trajectories across the time course of vowel production. Vowel duration is compared across short and long vowel categories of all five qualities in both languages. The relationship of fundamental frequency to vowel identity and phonation type is investigated.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".