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Record W2200282337 · doi:10.1056/jp200807140000001

Emerging Perspectives: Psychotropic Drugs During Pregnancy — New Data on Neonatal Outcomes

2008· article· en· W2200282337 on OpenAlexaboutno aff
Peter Roy‐Byrne

Bibliographic record

VenueJournal watch · 2008
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVenlafaxineParoxetinePregnancyAntidepressantPsychiatrySertralineObservational studyAnxietyMoodMood disordersFluoxetinePediatricsObstetricsInternal medicine

Abstract

fetched live from OpenAlex

We still know little about the neonatal risks from maternal use of psychotropic drugs during pregnancy, which limits accurate weighing of risks and benefits for expectant mothers. Three big observational studies provide new data. Using large medical, demographic, and public drug insurance registries in Quebec, researchers focused on women with psychiatric diagnoses (mostly, mood or anxiety disorders) and antidepressant use for at least 1 month in the year before pregnancy. Researchers compared first-trimester antidepressant exposure and duration in 2140 healthy infants and 189 infants with any major congenital malformation in the year after birth. Antidepressants commonly used were paroxetine (42%), sertraline (15%), and venlafaxine (13%). The risk for congenital malformation (8%, vs. …

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)0.010
metaresearch head score (Gemma)0.031
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: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.031
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0000.002
Scholarly communication0.0020.006
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.042
GPT teacher head0.344
Teacher spread0.301 · 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
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

Citations0
Published2008
Admission routes1
Has abstractyes

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