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Record W2177389719 · doi:10.7205/milmed-d-14-00258

The Effects of Prenatal Vitamin Supplementation on Operationally Significant Health Outcomes in Female Air Force Trainees

2015· article· en· W2177389719 on OpenAlexaff
Kirsten Barnes, Juste N. Tchandja, Bryant J. Webber, Susan P. Federinko, Thomas L. Cropper

Bibliographic record

VenueMilitary Medicine · 2015
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsCanadian Armed Forces
Fundersnot available
KeywordsAttritionMedicineIncidence (geometry)AnemiaConfidence intervalStatistical significancePregnancyIron supplementationVitamin D and neurologyPediatricsPhysical therapyIron deficiencyInternal medicineDentistry

Abstract

fetched live from OpenAlex

OBJECTIVES: A prenatal vitamin supplementation program for female basic military trainees at Joint Base San Antonio-Lackland was initiated in June 2012 with the goals of decreasing attrition and improving performance. This project examined whether supplementation influences attrition rates, incidence of stress fractures and iron deficiency anemia, and physical performance. METHODS: This was a cohort-based pilot study with an historical control group. Primary outcome measures included all-cause attrition, medical attrition, stress fractures, and iron deficiency anemia. RESULTS: Incidence rates of all-cause attrition, medical attrition, stress fractures, and anemia were similar in both groups, although the lower medical attrition in the supplementation group approached statistical significance (risk ratio, 0.74; 95% confidence interval, 0.54-1.01). CONCLUSION: Although this study found no statistical benefit, the operationally significant reduction in medical attrition of 26% suggests that providing prenatal vitamin supplementation to female basic trainees in the Air Force may be worthwhile.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.131
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.055
GPT teacher head0.435
Teacher spread0.381 · 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 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

Citations9
Published2015
Admission routes1
Has abstractyes

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