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Record W4394524757 · doi:10.6084/m9.figshare.7710908

The effect of vitamin D on cognitive functions in young female patients: a prospective controlled study using the Montreal Cognitive Assessment

2019· dataset· en· W4394524757 on OpenAlexaboutno aff
Özlem Balbaloğlu, Nermin Tanık

Bibliographic record

VenueFigshare · 2019
Typedataset
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentCognitionCognitive Assessment SystemMedicineProspective cohort studyGerontologyPsychologyCognitive impairmentInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

ABSTRACT Aim: Our aim was to determine whether there is a relationship between vitamin D [25(OH)D] and cognitive functioning in women with low 25(OH)D levels. Methods: Ninety female patients, 25-45 years of age, who attended our outpatient clinic and had 25(OH)D levels < 30 ng/mL, were included. The Montreal Cognitive Assessment (MoCA) scale was used to determine cognitive functioning; the scale is divided into seven subgroups. Patients were divided into three subgroups according to their 25(OH)D levels. After a three-month period of 25(OH) D replacement, the patients underwent a re-evaluation using the MoCA scale. Results: The total MoCA score before treatment was significantly different from the score after treatment (p < 0.05). Language and delayed recall functions were significantly different before and after treatment (p < 0.05). Conclusion: Vitamin D levels were related to cognitive functioning in our study group.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.033
GPT teacher head0.366
Teacher spread0.333 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2019
Admission routes1
Has abstractyes

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