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Record W2618299649 · doi:10.15173/m.v1i25.853

Chronic Kidney Disease of Unknown Etiology and the Island of Widows

2014· article· en· W2618299649 on OpenAlexaffvenue
Arun C.R. Partridge, Louise Chong

Bibliographic record

VenueThe Meducator · 2014
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsMcMaster University
Fundersnot available
KeywordsEtiologyKidney diseaseDiseaseMedicinePeer reviewInternal medicineBiology

Abstract

fetched live from OpenAlex

We recently had the opportunity to spend 3 months working with La Isla Foundation (LIF), a non-governmental organization that aims to raise awareness and combat the Chronic Kidney Disease of Unknown Etiology Epidemic (CKDu) ravaging regions of Nicaragua. This epidemic has not received the international coverage and awareness that it deserves, but recent research studies and news articles have been published which have drawn global attention. There have been multiple anecdotal reports of a high chronic kidney disease prevalence in rural parts of Nicaragua and El Salvador. We assisted La Isla Foundation in their work, contributing to a variety of community development, public health, and human rights projects which gave us exposure to the important cause for which they fight.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.614
Threshold uncertainty score0.211

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.247
Teacher spread0.241 · 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 teacher head, 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
Published2014
Admission routes2
Has abstractyes

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