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Record W2982798288 · doi:10.35451/jkf.v2i1.181

ANALISIS KADAR VITAMIN D PADA MAHASISWA INSTITUT KESEHATAN MEDISTRA DAN MAHASISWA FAKULTAS KEDOKTERAN GIGI UNIVERSITAS SUMATERA UTARA

2019· article· en· W2982798288 on OpenAlexaboutno aff
Miftahul Zannah, Yahwardiah Siregar, Ariyati Yosi

Bibliographic record

VenueJURNAL KEPERAWATAN DAN FISIOTERAPI (JKF) · 2019
Typearticle
Languageen
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsnot available
Fundersnot available
KeywordsVitamin D and neurologyMedicinevitamin D deficiencyVitaminInternal medicine

Abstract

fetched live from OpenAlex

Vitamin D levels influenced by many factors like formation, nutritions, malabsorbtion and degradation of 25(OH)D. Formation factors is one of important for metabolism vitamin D. Vitamin D is the main hormone regulating calcium phosphate homeostasis and mineral bone metabolism. Loss of muscle mass and fraity are prevalent in many chronic disease. The study group consisted of 31 samples from Institut Kesehatan Medistra (n=12) and Fakultas Kedokteran Gigi USU (n=19). Vitamin D levels were measure with ELISA (Diagnostic Biochem Canada). Most age for student Institut Kesehatan Medistra is 21 years old and student Fakultas Kedokteran Gigi USU is 22 years old. Frequency of Vitamin D level student Institut Kesehatan Medistra is 91,7% (deficiency) and student Fakultas Kedokteran Gigi USU 84,2%(deficiency). There was significant difference in vitamin D levels between two group with significant (p=0,018).

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.437
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.261
Teacher spread0.249 · 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.

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

Citations0
Published2019
Admission routes1
Has abstractyes

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