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Record W2586880812 · doi:10.1093/ndt/gfw122.01

SO028CALCITRIOL SUPPLEMENTATION INCREASES VON WILLEBRAND FACTOR LEVELS, FIBROBLAST GROWTH FACTOR-23 LEVELS, AND VASCULAR CALCIFICATION SEVERITY IN EXPERIMENTAL CHRONIC KIDNEY DISEASE

2016· article· en· W2586880812 on OpenAlexaff
Cynthia M. Pruss, Bruno Svajger, Jason G.E. Zelt, Kimberly Laverty, Emilie Ward, Rachel M. Holden, Michael A. Adams

Bibliographic record

VenueNephrology Dialysis Transplantation · 2016
Typearticle
Languageen
FieldMedicine
TopicParathyroid Disorders and Treatments
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineFibroblast growth factor 23Kidney diseaseVon Willebrand factorInternal medicineCalcificationEndocrinologyGrowth factorPlateletCalciumReceptorParathyroid hormone

Abstract

fetched live from OpenAlex

Introduction and Aims: The treatment of hyperparathyroidism with calcitriol in CKD may develop cardiovascular disease induced by endothelial dysfunction and vascular calcification. This study examines the effects of the dosage and frequency of administration of calcitriol in an animal model of CKD. Methods: Male Sprague Dawley rats were fed a CKD diet (1% phosphate, 0.25% adenine) for 7 weeks. At week 3, animals began calcitriol treatment: CKD (0 calcitriol, n=8), 20CAL, 80CAL, (20 or 80 ng/kg/ calcitriol, once/day), 5CAL-QID, 20CAL-QID (5 or 20 ng/kg 4/day calcitriol, n=8) or CON (healthy control, N=6). CKD severity (serum creatinine), calcification (tissue levels of calcium and phosphate), and plasma levels of intact parathyroid hormone (PTH), C-term fibroblast growth factor 23 (FGF-23), and von Willebrand factor (VWF, a marker of endothelial dysfunction) were measured. Statistics are reported as mean ± st. dev. for normal data or median (range), one way ANOVA with Tukey post-test, and Pearson correlations.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.276
Teacher spread0.258 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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