Bibliographic record
Abstract
PURPOSE OF REVIEW: The purpose of this study is to review the relevant literature concerning work-associated irritable larynx syndrome (WILS), a hyperkinetic laryngeal disorder associated with occupational irritant exposure. Clinical symptoms are variable and include dysphonia, cough, dyspnoea and globus pharyngeus. WILS is a clinical diagnosis and can be difficult to differentiate from asthma. Treatment options for WILS include medical and behavioural therapy. RECENT FINDINGS: Laryngeal-centred upper airway symptoms secondary to airborne irritants have been documented in the literature under a variety of diagnostic labels, including WILS, vocal cord dysfunction (VCD), laryngeal hypersensitivity and laryngeal neuropathy and many others. The underlying pathophysiology is as yet poorly understood; however, the clinical scenario suggests a multifactorial nature to the disorder. More recent literature indicates that central neuronal plasticity, inflammatory processes and psychological factors are all likely contributors. SUMMARY: Possible mechanisms for WILS include central neuronal network plasticity after noxious exposure and/or viral infection, inflammation (i.e. reflux disease) and intrinsic patient factors such a psychological state. Treatment is individualized and frequently includes one or more of the following: environmental changes in the workplace, GERD therapy, behavioural/speech therapy, psychotherapy counselling and neural modifiers.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".