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Record W3199176382 · doi:10.1192/bjo.2021.1010

Depression in pregnant women with and without COVID-19

2021· article· en· W3199176382 on OpenAlex
Alissa Papadopoulos, Emily S. Nichols, Yalda Mohsenzadeh, Isabelle Giroux, Michelle F. Mottola, Ryan J. Van Lieshout, Emma G. Duerden

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBJPsych Open · 2021
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsMcMaster UniversityInstitut du Savoir MontfortChildren’s Health Research InstituteUniversity of OttawaWestern University
FundersCanada First Research Excellence Fund
KeywordsCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)PregnancyDepression (economics)MedicinePsychologyObstetricsVirologyInternal medicineBiologyEconomicsOutbreakKeynesian economicsInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Evidence suggests that pregnant women who test positive for COVID-19 may develop more severe illness than non-pregnant women and may be at greater risk for psychological distress. The relationship between COVID-19 status (positive, negative, never tested) and symptoms of depression was examined in a survey study (May to September 2020) of pregnant women ( n = 869). Pregnant women who reported testing positive for COVID-19 were significantly more likely to report depressive symptoms compared with women who tested negative ( P = 0.027) and women who were never tested ( P = 0.005). Findings indicate that pregnant women who test positive for COVID-19 should be screened and monitored for depressive symptoms.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.330

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 head0.044
GPT teacher head0.377
Teacher spread0.333 · 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