MétaCan
Menu
Back to cohort
Record W2965899533 · doi:10.1016/j.ekir.2019.07.017

Association Between Perfluoroalkyl Substance Exposure and Renal Function in Children With CKD Enrolled in H3Africa Kidney Disease Research Network

2019· article· en· W2965899533 on OpenAlexaboutno aff
Shefali Sood, Akinlolu Ojo, Dwomoa Adu, Kurunthachalam Kannan, Akhgar Ghassabian, Tony T. Koshy, Suzanne Vento, Laura Jane Pehrson, Joseph Gilbert, Fatiu A. Arogundade, Adebowale Ademola, Babatunde Salako, Y R Raji, Charlotte Osafo, Sampson Antwi, Howard Trachtman, Leonardo Trasande, Samuel Ajayi, David Burke, Richard Cooper, Rasheed Gbadegesin, Titilayo O. Ilori, Manmak Mamven, Timothy O. Olanrewaju, Rulan S. Parekh, Jacob Plange Rhule, Tunde Salako, Bamidele O. Tayo, Ifeoma Ulasi

Bibliographic record

VenueKidney International Reports · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Human Genome Research Institute
KeywordsMedicineRenal functionKidney diseaseAssociation (psychology)DiseaseInternal medicineIntensive care medicine

Abstract

fetched live from OpenAlex

The prevalence of chronic kidney disease (CKD) is increasing at an accelerated pace in countries with limited health resources compared to developed countries.1 There is a need for more studies of the epidemiology and clinical characteristics of CKD in pediatric populations in sub-Saharan Africa, where risk factors are common.2

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)0.004
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 score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.262
Teacher spread0.251 · 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

Citations10
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueKidney International ReportsSame topicPer- and polyfluoroalkyl substances researchFrench-language works237,207