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Record W2152489878 · doi:10.1080/140154302760409293

Hidden respiratory allergies in voice users: treatment strategies

2002· article· en· W2152489878 on OpenAlexaff
Cristina Jackson‐Menaldi, Andrew I. Dzul, R. Wayne Holland

Bibliographic record

VenueLogopedics Phoniatrics Vocology · 2002
Typearticle
Languageen
FieldMedicine
TopicMusicians’ Health and Performance
Canadian institutionsLakeshore General Hospital
Fundersnot available
KeywordsMedicineAllergyLarynxLaryngitisDesensitization (medicine)AirwayAsthmaDermatologyAnesthesiaImmunologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

The treatment of the allergic voice patient may be somewhat different than other voice patients. Antihistamines are generally avoided, though decongestants with Guaifenesin may be useful. Steroids are more useful in perennial allergic systems. Steroids may be inhaled nasally, inhaled orally, or given systemically. Systemic steroids are especially useful for a performer who needs quick relief. We strongly feel that vocalists with chronic laryngitis and dysphonia should be allergy tested. A hidden dust mite or cat dander allergy is often found. A clean indoor environment can then be established. Immunotherapy injections can also be initiated. Both of these treatments, desensitization injections and environmental control, are especially useful in vocalists. These treatments are helpful in keeping a vocalist's trachea, larynx, and nasal cavity healthy. A careful search for mild asthma should be considered. Establishing good vocal hygiene and voice training may also be necessary.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0100.002

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.

Opus teacher head0.069
GPT teacher head0.325
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2002
Admission routes1
Has abstractyes

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