Vocal changes across disease progression in amyotrophic lateral sclerosis (ALS)
Bibliographic record
Abstract
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by loss of muscle strength and function. The speech systems (respiratory, phonatory, velopharyngeal, and articulatory) are frequently affected, causing speech and swallowing impairments. Changes to voice production are often reported. These changes include altered fundamental frequency, phonatory instability, and the development of breathy or harsh voice quality (see Green et al., 2013 for review). While acoustic studies of speakers with ALS have demonstrated voice dysfunction, the findings have been variable in the type and direction of change across individual speakers. The current investigation seeks to further explicate vocal dysfunction and change in ALS by exploring promising acoustic phonatory measures across disease progression. Participants with and without ALS were audiorecorded at multiple time points while producing sustained vowels and connected speech. Acoustic analyses include traditional phonatory measures extracted from vowel prolongations (fundamental frequency, jitter, and shimmer) and newer measures of phonation across connected speech (e.g., cepstral peak prominence). Voice metrics are compared between speaker groups and across time points. It is anticipated that the findings will support the development of valid and reliable measures to mark disease onset and progression, thereby facilitating intervention and mitigating the devastating impact of ALS.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".