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Record W3138617394 · doi:10.1002/9781119606987.ch15

Children with Speech Sound Disorders

2021· other· en· W3138617394 on OpenAlexaff
Susan Rvachew

Bibliographic record

Venuenot available
Typeother
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsMcGill University
Fundersnot available
KeywordsBabblingSpeech soundComputer scienceAudiologySpeech-Language PathologySpeech recognitionProcess (computing)PsychologyMedicineLinguistics

Abstract

fetched live from OpenAlex

Key markers of normal speech development include babbling in the first year, attainment of intelligible meaningful speech by the age of 4 years, and adult-like speech accuracy at age 9 years. Many children do not achieve these speech acquisition milestones at the expected rate and are thus diagnosed with a speech sound disorder (SSD). This chapter is concerned with primary SSDs. Then, a brief outline of normal speech development is provided. Even in the case of primary SSD, diagnosis and treatment planning requires an understanding of possible proximal causes, and therefore a thorough investigation of hearing, phonological processing, and oral-motor structure and function is also required. The clinical management of SSDs by the speech-language pathologist (SLP) is covered. The process for assessing a child who has been referred due to suspected speech problems is necessarily comprehensive due to the nature of questions that must be answered by the SLP.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.311
Threshold uncertainty score0.999

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)0.3120.001

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 head0.008
GPT teacher head0.266
Teacher spread0.258 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2021
Admission routes1
Has abstractyes

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