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Record W30489256 · doi:10.7554/elife.37161

Этнические особенности липидного и углеводного обменов у больных сахарным диабетом i типа

2006· article· ru· W30489256 on OpenAlexfundno aff
Л. И. Колесникова, Т. П. Бардымова, В. А. Петрова, М. И. Долгих, М. А. Даренская, Lyudmila Grebenkina, Л. В. Натяганова

Bibliographic record

VenueCyberLeninK (CyberLeninka) · 2006
Typearticle
Languageru
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesNational Institutes of HealthNational Cancer InstituteCanadian Institutes of Health ResearchVirginia and D.K. Ludwig Fund for Cancer ResearchBreast Cancer Research Foundation
KeywordsLactic acidType 2 diabetesPopulationDiabetes mellitusMedicineInternal medicineChemistryGastroenterologyEndocrinologyBiologyBacteria

Abstract

fetched live from OpenAlex

Sixty-five patients of the Russian and Buryat nationalities having I type diabetes were examined. All patients examined were born in Buryat republic and were living there. It was revealed that the changes in indices of lipidogramms in patients of Russian population are atherogenic variant of dislipidemia. In this patients' group there was registered reliable increase of primary LP products double bonds and diene conjugates for 31 and 34 % accordingly in comparison with the I type diabetes patients of Buryat nationality. During the analysis of the indices of carbohydrate metabolism in the control and patients' groups there was found reliable increase of lactic acid level and ratio of lactic acid /pyruvic acid in patients of Russian population. Lactic acid content and ratio of lactic acid /pyruvic acid in this group increased by 2.4.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.005

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 head0.008
GPT teacher head0.234
Teacher spread0.226 · 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 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
Published2006
Admission routes1
Has abstractyes

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