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Record W1769545231 · doi:10.1002/pbc.25017

Updates on histiocytic disorders

2014· article· en· W1769545231 on OpenAlexaff
Sarah R. Vaiselbuh, Yenan T. Bryceson, Carl E. Allen, James A. Whitlock, Oussama Abla

Bibliographic record

VenuePediatric Blood & Cancer · 2014
Typearticle
Languageen
FieldMedicine
TopicHistiocytic Disorders and Treatments
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsMedicineHistiocyteHemophagocytic lymphohistiocytosisLangerhans cell histiocytosisBlood cancerHistiocytosisHematologyDiseaseRosai–Dorfman diseaseCancerMalignant histiocytosisRare diseasePathologyImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Histiocytic disorders are rare entities that are becoming more recognized as our understanding of the molecular pathogenesis lead to novel diagnostic tests and targeted drug development. A symposium held at the American Society of Pediatric Hematology/Oncology (ASPHO) 2013 Annual Meeting discussed new insights into histiocytic disorders. This review highlights the symposium presentations, divided into three sections encompassing Langerhans cell histiocytosis (LCH), hemophagocytic lymphohistiocytosis (HLH) and Rosai Dorfman disease (RDD) including subsections on pathogenesis, clinical diagnostic criteria and novel insights into treatment. Details of other histiocytic disorders as well as the standard treatment guidelines have been published elsewhere and are beyond the scope of this discussion [Haupt et al. (2013). Pediatr Blood Cancer 60:175-184; Henter et al. (2007). Pediatr Blood Cancer 48:124-131].

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)0.005
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: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0190.009

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 head0.006
GPT teacher head0.251
Teacher spread0.245 · 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
GenreReview

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

Citations121
Published2014
Admission routes1
Has abstractyes

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