Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper looks at the acoustics of uvulars in Tlingit, an Athabaskan language spoken in Alaska and Canada. Data from five native speakers was used for acoustic analysis for tokens from five phoneme groups (alveolars, plain velars, labialized velars, plain uvulars, and labialized uvulars). The tokens were analyzed by computing spectral moments of plosive bursts and fricatives, and F2 and F3 values for post-consonantal vowels, which were used to calculate locus equations, a descriptive measure of the relationship between F2 at vowel onset and midpoint. Several trends were observed, including a greater difference between F2 and F3 after uvulars than after velars, as well as a higher center of gravity (COG) and lower skew and kurtosis for uvulars than for velars. The comparison of plain versus labialized consonants supports the finding of Suh (2008) that labialization lowers mean burst energy, or COG, and additionally found labialization to raise skew and kurtosis.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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