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Record W2094013752 · doi:10.1155/2013/712758

What We Have Learned about Autism Spectrum Disorder from Valproic Acid

2013· review· en· W2094013752 on OpenAlexafffund
Taylor Chomiak, Nathanael Reid Turner, Bin Hu

Bibliographic record

VenuePathology Research International · 2013
Typereview
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsValproic AcidAutism spectrum disorderMedicineBroad spectrumAutismNeurodevelopmental disorderEpidemiologyNeuroscienceAnimal studiesPsychiatryEpilepsyPathologyPsychologyInternal medicine

Abstract

fetched live from OpenAlex

Two recent epidemiological investigations in children exposed to valproic acid (VPA) treatment in utero have reported a significant risk associated with neurodevelopmental disorders and autism spectrum disorder (ASD) in particular. Parallel to this work, there is a growing body of animal research literature using VPA as an animal model of ASD. In this focused review we first summarize the epidemiological evidence linking VPA to ASD and then comment on two important neurobiological findings linking VPA to ASD clinicopathology, namely, accelerated or early brain overgrowth and hyperexcitable networks. Improving our understanding of how the drug VPA can alter early development of neurological systems will ultimately improve our understanding of ASD.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.950
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0050.003
Research integrity0.0010.006
Insufficient payload (model declined to judge)0.0160.025

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 head0.228
GPT teacher head0.472
Teacher spread0.244 · 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 designOther design
Domainnot available
GenreReview

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

Citations118
Published2013
Admission routes2
Has abstractyes

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