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Record W2602281681 · doi:10.1136/eb-2016-102578

Largest study to date shows overall use of antipsychotics in pregnancy does not appear to significantly increase the risk of congenital malformations

2017· letter· en· W2602281681 on OpenAlexaff
Sophie Grigoriadis, Miki Peer

Bibliographic record

VenueEvidence-Based Mental Health · 2017
Typeletter
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsCongenital malformationsMedicinePregnancyObstetricsHigh risk pregnancyPediatricsBiologyGenetics

Abstract

fetched live from OpenAlex

Atypical and typical antipsychotics (APs) are used to treat bipolar and psychotic disorders, and atypicals are increasingly used off-label to treat other disorders. 1With the rise of their use during pregnancy, we are increasingly in need of high-quality data to rely on for treatment recommendations as data from randomised controlled trials (RCT) are not available.Previous research on whether APs are associated with an increased risk of congenital malformations (CMs) has not yielded consistent findings and has relied on a small number of exposures. [2][3]][4] Given the small baseline risk for CMs in the general population and the large number of potential confounders, very large sample sizes are needed in observational studies assessing the link between APs and CMs.e7

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.084
GPT teacher head0.358
Teacher spread0.273 · 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 teacher head, not a consensus.

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
Published2017
Admission routes1
Has abstractyes

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