Bibliographic record
Abstract
This paper aimed to establish preliminary normative data scores of nasalance value for the Arab Emirati speakers, and to compare them to other Arabic speakers, particularly the Saudi, Jordanian and Egyptian speakers. Design was a cross-sectional study where nasality scores (nasalance percentages) were obtained under oral and vowel passage tasks. Participants were 104 Emirati individuals (54 males, age range 18-27, and 50 females, age range 18-27). Each participant was asked to extend the /a:/ vowel and read a passage in Arabic. A nasometer model II, 6450 (KayPentax, Canada) was utilized for nasalance scores computation. The ANOVA revealed no significant differences between the female and male Emirati speakers’ nasalance scores in both the vowel (males= 26.35, females= 23.3) and the oral passage tasks (males= 15, females= 15.1). The Emirati speakers had higher nasalance scores than the Saudi speakers in both tasks, and in the /a:/vowel task compared to the Egyptian and Jordanian speakers. Language and dialect are two important variables in determining the nasalance normative scores..
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".