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Record W2169008779 · doi:10.1177/1088357609334057

Using Discrete Trial Instruction to Teach Children With Angelman Syndrome

2009· article· en· W2169008779 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFocus on Autism and Other Developmental Disabilities · 2009
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAngelman syndromePsychologyAutismIntellectual disabilityDevelopmental psychologyCognitionRett syndromeEtiologyClinical psychologyAudiologyPsychiatryMedicine

Abstract

fetched live from OpenAlex

Discrete trial instruction (DTI) was used to teach functional skills to three children with Angelman syndrome, a neurogenetic disorder that overlaps with autism and is associated with severe cognitive, speech, and motor impairments. Children received individual DTI teaching sessions 2 to 3 times per week over a 12-month period and displayed differing rates and patterns of skill development. Parents expressed positive views toward the DTI methods and their clinical outcomes. The results of this case series provide preliminary data suggesting that these strategies are appropriate for building functional skills in some children with Angelman syndrome and possibly other groups of children with severe/profound intellectual disability with different etiologies.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score0.854

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 head0.039
GPT teacher head0.294
Teacher spread0.255 · 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