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Record W2102849275 · doi:10.1002/dev.21086

The effects of vitamin D<sub>3</sub> during pregnancy and lactation on offspring physiology and behavior in Sprague–Dawley rats

2012· article· en· W2102849275 on OpenAlexaff
Pauline Pan, Daniel H.S. Jin, Munmun Chatterjee‐Chakraborty, Katherine Halievski, Daeria O. Lawson, David Remedios, Cassandra Smetka, Vânia Lopes Pinto, Esteban J. Parra, Alison S. Fleming

Bibliographic record

VenueDevelopmental Psychobiology · 2012
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsCentre for Addiction and Mental HealthUniversity of Toronto
Fundersnot available
KeywordsOffspringWeaningLactationPregnancyPhysiologyVitaminVitamin D and neurologyEndocrinologyInternal medicineDevelopmental psychologyAnxietyPsychologyBiologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

Recent findings show that developmental vitamin D deficiency leads to altered brain morphology and behavioral development in the rat offspring. We examined the effects of different dietary vitamin D levels in rat dams on behavior and biochemistry of the offspring. Females were divided into five conditions and received diets containing 0, 1,5, 3.3, 6.0, or 10.0 IU/g of vitamin D₃ from mating to weaning. Offspring were tested as juveniles and as adults for anxiety, social learning and behavior, and locomotion. Results show that both deficient and excessive levels of vitamin D3 in juveniles lead to altered physiology and behavior. In juveniles but not adults, variations in vitamin D were related to variations in measures of anxiety and marginally, activity levels. For social behaviors, both juveniles and adults were affected by mothers' diets. In general, offspring of animals receiving abnormal concentrations of vitamin D showed the most deficits.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.287
Teacher spread0.274 · 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 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

Citations28
Published2012
Admission routes1
Has abstractyes

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