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Record W4414974936 · doi:10.1177/27325016251378622

Normative Nasalance Scores for French-Speaking Children in Quebec: A Tale of 2 Cities

2025· article· en· W4414974936 on OpenAlexaffabout
Ericka Beaudoin, Annie Salois, Andréanne Mayrand, Johanie Bouchard, Lisa Massaro, Élisa-Maude McConnell, Tim Bressmann, Marie‐Ève Caty

Bibliographic record

VenueFACE · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCleft Lip and Palate Research
Canadian institutionsUniversité du Québec à Trois-RivièresUniversity of TorontoCentre hospitalier universitaire de QuébecMontreal Children's HospitalCentre Hospitalier Universitaire Sainte-JustineUniversité LavalMcGill University Health Centre
Fundersnot available
KeywordsNormativeNasalityNasal passagesReference valuesTest (biology)Statistical analysis

Abstract

fetched live from OpenAlex

Objective: To establish normative nasalance scores for the Nasometer II for children speaking Quebec French. Design: Prospective study using a randomly selected sample of children with typical speech. Setting: Two children’s hospitals in the province of Quebec, Canada. Participants: Eighty-eight children with typical speech, language and hearing development, aged between 6;00 and 11;11 years, were enrolled at the Centre hospitalier universitaire Sainte-Justine in Montreal and the Centre hospitalier universitaire de Québec-Université Laval in Quebec City, Canada. Outcome Measure: Mean nasalance scores. Results: Mean nasalance scores were obtained for oral vowels, nasal vowels, repeated syllables, oral sentences, a nasal sentence, mixed sentences as well as a short text. While there were no meaningful significant effects of sex and age on the nasalance scores, most nasalance scores obtained at the hospital site in Montreal were statistically significantly higher than in Quebec City. Mean nasalance scores, standard deviations and theoretical critical threshold values are provided and can be used for clinical assessment and research. Conclusions: Nasalance scores differences according to hospital sites may be attributable to dialectal differences, to differences between the nasalance scores obtained by the nasometers in the 2 clinics, or to a combination of the 2. In future research, diagnostic cutoff scores for different nasal resonance disorders can be developed based on these normative scores.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.286
Teacher spread0.277 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2025
Admission routes2
Has abstractyes

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