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Record W7009328258

Down syndrome and childhood apraxia of speech: matching a unique psycholinguistic profile to an effective treatment program

2016· dissertation· en· W7009328258 on OpenAlexfundno aff

Bibliographic record

VenueOpen MIND · 2016
Typedissertation
Languageen
FieldEnvironmental Science
TopicHydrology and Drought Analysis
Canadian institutionsnot available
FundersFaculty of Medicine, McGill UniversityMcGill University
KeywordsIntelligibility (philosophy)ApraxiaDown syndromePhonological DisorderDysarthriaVoice-onset timeTypically developingMatching (statistics)Speech disorder
DOInot available

Abstract

Three single subject experiments were conducted to explore the response by individuals with Down Syndrome (DS) to different treatments for the remediation of speech impairments. Although the speech impairment in DS is typically described as dysarthria, a growing body of research suggests that there may be concomitant childhood apraxia of speech (CAS) and phonological disorders that explain poor speech accuracy and intelligibility in these individuals. The appropriate treatment to remediate speech impairment in DS may depend upon each individual's psycholinguistic profile. Three single subject randomized experiments were conducted with participants ranging in age from 10-20 years. For each experiment, two treatment conditions were compared to a control condition: the experimental conditions addressed the underlying deficits associated with either CAS (a motor planning impairment) or Inconsistent Phonological Disorder (a phonological planning impairment). High intensity treatment was undertaken with each participant receiving a total of 18 treatment sessions in six to nine weeks. In each study, the results indicate improvement in speech accuracy but with varying response across participants to specific treatment approaches. Follow-up assessments with each participant demonstrate maintenance of learning over time. Each participant's specific response to treatment is discussed in relation to their psycholinguistic profile as revealed by their pre-treatment assessment results.

Stored with the screening record, where it is evidence for the labels above.

How this classification was reachedexpand

The three-model screen

all 5,600 screened works →

All three models called this out of scope.

stratum: fund_new · design weight: 1678.90 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: empirical
about Canada: no
confidence: high

Single-subject treatment experiments for speech impairment in Down syndrome; the object is a clinical intervention.

GPT-5.6 (high)OUT
genre: empirical
about Canada: no
confidence: high

The dissertation evaluates speech treatments for people with Down syndrome, not research itself.

Grok 4.5OUT
genre: empirical
about Canada: no
confidence: high

Clinical speech therapy experiments for Down syndrome; clinical domain intervention study.

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)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.319
Teacher spread0.309 · 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
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

Citations0
Published2016
Admission routes1
Has abstractyes

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