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Record W7162134813 · doi:10.82308/47832

Effect of caffeine intake during pregnancy on the risk of intrauterine growth retardation

2001· dissertation· en· W7162134813 on OpenAlexaboutno aff
Isabelle. Chevalier

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicCoffee research and impacts
Canadian institutionsnot available
Fundersnot available
KeywordsCaffeinePregnancyGrowth retardationGestational ageBirth weightCase-control study

Abstract

fetched live from OpenAlex

We estimated the effect of caffeine intake from tea, coffee, and colas on the risk of mild and severe intrauterine growth retardation (IUGR) through a case-control study in 500 live singleton infants born at Sainte-Justine Hospital, in Montreal, between May 1998 and July 2000. Cases of IUGR as well as one sex, race and gestational age-matched control per case were identified at birth. Data were abstracted from medical charts and post-delivery questionnaires, and were analysed using conditional logistic regression. Average caffeine intake in pregnancy was not a significant predictor of mild or severe IUGR (for mild IUGR, OR for >300 mg/day of caffeine vs. none:1.21, 95%CI [0.33, 4.40]; trend: p = 0.28). Moderate first-trimester caffeine use significantly increased the risk of mild (OR 2.41, 95%CI [1.01, 5.75]), but not severe, IUGR. Reduction of caffeine use at the onset of pregnancy was protective for mild and severe IUGR (OR 0.34, 95%CI [0.13, 0.92], and 0.55, 95%CI [0.32, 0.94], respectively).

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.073
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.306
Teacher spread0.294 · 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 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
Published2001
Admission routes1
Has abstractyes

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