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Record W7100429053

Research Article Limiting Excess Weight Gain in Healthy Pregnant Women: Importance of Energy Intakes, Physical Activity, and Adherence to Gestational Weight Gain Guidelines

2016· article· en· W7100429053 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsnot available
Fundersnot available
KeywordsWeight gainOverweightPedometerPregnancyLimitingLogistic regressionGestationPhysical activityBody weight
DOInot available

Abstract

fetched live from OpenAlex

License, which permits unrestricted use, distribution, and reproduction in anymedium, provided the originalwork is properly cited. Few studies have investigated if compliance with energy intakes, physical activity, and weight gain guidelines attenuate postpartum weight retention (PPWR) inmothers attending prenatal classes.We investigated whether (a) daily energy intakes within 300 kcal of estimated energy requirements (EERs), (b) walkingmore than 5000 steps/day, (c) targeting the recommended weight gain goals for prepregnancy BMI, and/or (d) achieving weekly or total gestational weight gain (GWG) recommendations minimized PPWR in 54 women attending prenatal classes in Montreal/Ottawa, Canada. Participants completed a validated pregnancy physical activity questionnaire (PPAQ), 3 telephone-validated 24-hr dietary recalls, and wore a pedometer for one week. PPWR was measured 6 weeks after delivery. Results showed that 72 % had healthy prepregnancy BMIs. However, 52 % consumed>300 kcal/day in excess of their EER, 54 % exceeded recommended GWG, and more overweight (93%) than normal weight women (38%) cited nonrecommended GWG targets. Following delivery, 33 % were classified as overweight, and 17 % were obese. Multiple logistic regressions revealed that women targeting “recommended weight gain advice ” were 3 times more likely to meet total GWG recommendations (OR: 3.2,

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.348

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.096
GPT teacher head0.388
Teacher spread0.291 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2016
Admission routes1
Has abstractyes

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