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Maternal reports of morbidity during the index ALSPAC pregnancy

2022· preprint· en· W4307883135 on OpenAlexaff
Genette Ellis, Abigail Fraser, Jean Golding, Yasmin Iles‐Caven, Kate Northstone

Bibliographic record

VenueWellcome Open Research · 2022
Typepreprint
Languageen
FieldEnvironmental Science
TopicHealth, Environment, Cognitive Aging
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
FundersMedical Research CouncilUniversity of BristolWellcome TrustJohn Templeton Foundation
KeywordsPregnancyLongitudinal studyMedicineStorkLongitudinal dataPediatricsObstetricsFamily medicineDemography

Abstract

fetched live from OpenAlex

<ns4:p>Within the ALSPAC (Avon Longitudinal Study of Parents and Children) resource, information concerning the health of the mother during pregnancy is available from three sources: (i) computerised data collected by midwives after the birth of the baby, known as the STORK database; (ii) data abstracted by ALSPAC staff from detailed medical obstetric records, and (iii) reports by mothers during pregnancy, and shortly after the birth using structured questionnaires completed at home. In this Data Note we focus on source (iii), and detail the information obtained from these mothers concerning their health, signs and symptoms together with medications and supplements taken during pregnancy. We also describe how the data can be accessed.</ns4:p>

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)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0040.037
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0400.000

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 head0.126
GPT teacher head0.401
Teacher spread0.275 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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