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Record W2937533962 · doi:10.1136/ebnurs-2019-103073

Preventing postpartum depression: fatigue management is a place to start

2019· letter· en· W2937533962 on OpenAlex

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.

Bibliographic record

VenueEvidence-Based Nursing · 2019
Typeletter
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsChildbirthDepression (economics)Postpartum depressionPsychological interventionAffect (linguistics)PsychologyMeta-analysisMedicinePostpartum periodClinical psychologyPsychiatryPregnancy

Abstract

fetched live from OpenAlex

Commentary on: Wilson N, Lee JJ, Bei B. Postpartum fatigue and depression: a systematic review and meta-analysis. J Affect Disord 2019;246:224–33. A positive fatigue–depression correlation among postpartum women suggests a need to develop evidence-based interventions targeting fatigue. These interventions may be less stigmatising than depression treatment and could help prevent postpartum depression. The purpose of the study1 was to synthesise the relationship between postpartum fatigue and depression among parents in the first 2 years following childbirth. A meta-analysis was conducted on the correlation between fatigue …

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.638
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.065
GPT teacher head0.350
Teacher spread0.285 · 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