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Record W3131724246 · doi:10.1016/j.ekir.2021.02.007

Evaluation of the Reproductive Care Provided to Adolescent Patients in Nephrology Clinics: A Pediatric Nephrology Research Consortium Study

2021· article· en· W3131724246 on OpenAlexaff
Tetyana L. Vasylyeva, Shyanne Page-Hefley, Salem Almaani, Isabelle Ayoub, Abigail Batson, Michelle Hladunewich, Noel Howard, Hilda Fernández, Michelle M. O’Shaughnessy, Monica L. Reynolds, Shikha Wadhwani, Jarcy Zee, William E. Smoyer, Scott E. Wenderfer, Katherine Twombley

Bibliographic record

VenueKidney International Reports · 2021
Typearticle
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineKidney diseaseNephrologyFamily medicinePregnancyReproductive healthInternal medicinePopulationEnvironmental health

Abstract

fetched live from OpenAlex

Approximately 20 million of the 333 million persons living in the United States are adolescent females.1 However, studies examining the reproductive care provided to adolescent females with kidney disease are scarce. Adolescents with chronic kidney disease (CKD) are at a critical transition phase, and many issues arising during adolescence can directly or indirectly affect renal and reproductive outcomes,2,3 including the effect of hormonal contraception on kidney physiology, a higher frequency of menstrual irregularities in patients with CKD, the potential for teratogenicity from kidney disease medications, and the need for preconception counseling about the risks of pregnancy.

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)0.004
metaresearch head score (Gemma)0.015
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.070
GPT teacher head0.427
Teacher spread0.357 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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