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Draft consensus guidelines for diagnosis and treatment of Shwachman‐Diamond syndrome

2011· article· en· W2126366711 on OpenAlexaffabout
Yigal Dror, Jean Donadieu, Jutta Köglmeier, J.A. Dodge, Sanna Toiviainen‐Salo, Outi Mäkitie, Elizabeth N. Kerr, Cornelia Zeidler, Akiko Shimamura, Neil Shah, Marco Cipolli, Taco W. Kuijpers, Peter R. Durie, Johanna M. Rommens, Liesbeth Siderius, Johnson M. Liu

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBlood disorders and treatments
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsExocrine pancreatic insufficiencyMedicinePediatricsBone marrow failureIntensive care medicineDiseaseSkeletal surveyConsensus conferencePathologyBioinformaticsInternal medicineCystic fibrosisGeneticsBiologyStem cell

Abstract

fetched live from OpenAlex

Shwachman-Diamond syndrome (SDS) is an autosomal recessive disorder characterized by pancreatic exocrine insufficiency and bone marrow failure, often associated with neurodevelopmental and skeletal abnormalities. Mutations in the SBDS gene have been shown to cause SDS. The purpose of this document is to provide draft guidelines for diagnosis, evaluation of organ and system abnormalities, and treatment of hematologic, pancreatic, dietary, dental, skeletal, and neurodevelopmental complications. New recommendations regarding diagnosis and management are presented, reflecting advances in understanding the genetic basis and clinical manifestations of the disease based on the consensus of experienced clinicians from Canada, Europe, and the United States. Whenever possible, evidence-based conclusions are made, but as with other rare diseases, the data on SDS are often anecdotal. The authors welcome comments from readers.

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)0.020
metaresearch head score (Gemma)0.047
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 score0.020
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.047
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0050.003
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0080.002
Research integrity0.0110.011
Insufficient payload (model declined to judge)0.0090.009

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 head0.206
GPT teacher head0.372
Teacher spread0.166 · 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

Citations243
Published2011
Admission routes2
Has abstractyes

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