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Record W2001012062 · doi:10.1080/13682820701449943

Case study using ultrasound to treat //

2008· article· en· W2001012062 on OpenAlexaffabout
Geetanjalee Modha, Barbara May Bernhardt, Robyn Church, Penelope Bacsfalvi

Bibliographic record

VenueInternational Journal of Language & Communication Disorders · 2008
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of British ColumbiaSurrey Place CentreSunny Hill Health Centre for Children
Fundersnot available
KeywordsPsychologyPsychotherapist

Abstract

fetched live from OpenAlex

BACKGROUND: Ultrasound has shown promise as visual feedback in remediation of /r/. AIMS: To compare treatment for /r/ with and without ultrasound. METHODS & PROCEDURES: A Canadian English-speaking adolescent participated in a case study with a no treatment baseline, alternating treatment blocks with and without ultrasound and a final no treatment period. OUTCOMES & RESULTS: Formant values and trained listener ratings of speech samples indicated improvement in /r/ production, particularly after the introduction of ultrasound. CONCLUSIONS: Ultrasound appeared to facilitate the acquisition of /r/ for the participant. Large-scale studies are needed to evaluate ultrasound further.

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)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0040.003
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0080.005
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.074
GPT teacher head0.437
Teacher spread0.363 · 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 designCase report
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

Citations41
Published2008
Admission routes2
Has abstractyes

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