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Record W1593668494 · doi:10.1093/ndt/gfu090

Nephropathic cystinosis: an international consensus document

2014· article· en· W1593668494 on OpenAlexaff
Francesco Emma, Galina Nesterova, Craig B. Langman, Alain Labbé, Stéphanie Cherqui, Paul Goodyer, Mirian C. H. Janssen, Marcella Greco, Rezan Topaloğlu, Ewa Elenberg, Ranjan Dohil, Corinne Antignac, P Cochat, Frederick J. Kaskel, Aude Servais, Elke Wühl, Patrick Niaudet, W. van 't Hoff, WilliamA. Gahl, Elena Levtchenko

Bibliographic record

VenueNephrology Dialysis Transplantation · 2014
Typearticle
Languageen
FieldMedicine
TopicBiomedical Research and Pathophysiology
Canadian institutionsMcGill UniversityMontreal Children's Hospital
FundersNational Institutes of Health
KeywordsCystinosisMedicinePolitical scienceChemistry

Abstract

fetched live from OpenAlex

Cystinosis is caused by mutations in the CTNS gene (17p13.2), which encodes for a lysosomal cystine/proton symporter termed cystinosin. It is the most common cause of inherited renal Fanconi syndrome in young children. Because of its rarity, the diagnosis and specific treatment of cystinosis are frequently delayed, which has a significant impact on the overall prognosis. In this document, we have summarized expert opinions on several aspects of the disease to improve knowledge and provide guidance for diagnosis and treatment.

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)0.010
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0060.004

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 head0.016
GPT teacher head0.304
Teacher spread0.287 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations9
Published2014
Admission routes1
Has abstractyes

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