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Record W2151786049 · doi:10.1093/ndt/gfr252

Low birth weight and nephron mass and their role in the progression of chronic kidney disease: a case report on identical twins with Alport disease

2011· article· en· W2151786049 on OpenAlexaff
T. V. Rajan, Sean J. Barbour, Colin T. White, Adeera Levin

Bibliographic record

VenueNephrology Dialysis Transplantation · 2011
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsBC Children's HospitalSt. Paul's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineKidney diseaseAlport syndromeNephronDiseaseOffspringLow birth weightMonozygotic twinBirth weightInternal medicineKidneyRenal functionSiblingEndocrinologyPediatricsPhysiologyPregnancyGlomerulonephritisGeneticsBiology

Abstract

fetched live from OpenAlex

We report the outcomes of 47-year-old monozygotic twins with Alport syndrome, who share the same maternal and genetic factors; however, in adulthood have discordant trajectories in the decline of their renal function. The twin with the more rapid progression to renal failure was born with low birth weight (LBW), suggesting congenital nephron deficiency and increased susceptibility to progressive renal disease, despite having the same genetically inherited kidney condition. This 'natural experiment' adds further credence to the hypothesis that LBW contributes to the susceptibility to chronic kidney disease. We suggest further studies and surveillance for this high-risk group of infants in order to gain additional insights into the impact of perinatal factors such as LBW.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
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 spread0.250 · 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 designCase report
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

Citations14
Published2011
Admission routes1
Has abstractyes

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