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Record W2186476718 · doi:10.1155/2015/501829

Maternal and Pediatric Health Outcomes in relation to Gestational Vitamin D Sufficiency

2015· review· en· W2186476718 on OpenAlexaff
Stephen J. Genuis

Bibliographic record

VenueObstetrics and Gynecology International · 2015
Typereview
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsMedicineGestational diabetesPregnancyGestational agePrenatal careVitamin D and neurologyPediatricsGestationObstetricsvitamin D deficiencyFetusHealth careIntensive care medicineEnvironmental healthPopulationEndocrinology

Abstract

fetched live from OpenAlex

Juxtaposed with monumental improvement in maternal-fetal outcomes over the last century, there has been the recent emergence of rising rates of gestational complications including preterm birth, operative delivery, and gestational diabetes. At the same time, there has been a burgeoning problem with widespread vitamin D deficiency among populations of many developed nations. This paper provides a brief review of potential health outcomes recently linked to gestational vitamin D deficiency, including preterm birth, cesarean delivery, and gestational diabetes. Although immediate costs for obstetric complications related to gestational vitamin D insufficiency may be modest, the short- and long-term costs for pediatric healthcare resulting from such gestational complications may be enormous and present an enduring burden on healthcare systems. With increasing evidence pointing to fetal origins of some later life disease, securing vitamin D sufficiency in pregnancy appears to be a simple, safe, and cost-effective measure that can be incorporated into routine preconception and prenatal care in the offices of primary care clinicians. Education on gestational nutritional requirements should be a fundamental part of medical education and residency training, instruction that has been sorely lacking to date.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.605
Threshold uncertainty score0.871

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.050
GPT teacher head0.370
Teacher spread0.320 · 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
GenreReview

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

Citations12
Published2015
Admission routes1
Has abstractyes

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