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Record W3174527820 · doi:10.1108/amhid-09-2020-0020

Validation of Hagerman’s behavioral phenotype for fragile X syndrome among men with intellectual disability

2021· article· en· W3174527820 on OpenAlexaff
Jacques Bellavance, Catherine Mello

Bibliographic record

VenueAdvances in Mental Health and Intellectual Disabilities · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsFragile X syndromeIntellectual disabilityMedicineClinical psychologyChecklistOriginalityPsychologyPsychiatryDevelopmental psychologySocial psychology

Abstract

fetched live from OpenAlex

Purpose The behavioral phenotype of fragile X syndrome (FXS) and intellectual disability (ID) proposed by Hagermanet al.(2009) was primarily based on data from male children and teens. The purpose of this study was to promote a better understanding of how this condition manifests in adults. Design/methodology/approach A total of 18 men of FXS were paired with men with Down syndrome on the basis of age and level of ID. A screening checklist was created on the basis of existing scales and the Hagermanet al.(2009) behavioral phenotype and completed by care providers. Findings Five of the 12 features of the phenotype were significantly more present among men with FXS than in men with Down syndrome. Originality/value This study provides partial confirmation for Hagerman et al.’s (2009) behavioral phenotype of FXS among men with moderate ID and identified some traits that warrant further investigation.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.293
Teacher spread0.279 · 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 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
Published2021
Admission routes1
Has abstractyes

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