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Record W2531520225 · doi:10.1182/blood-2016-08-733790

Alternative genetic mechanisms of BRAF activation in Langerhans cell histiocytosis

2016· article· en· W2531520225 on OpenAlexaff
Rikhia Chakraborty, Thomas M. Burke, Oliver Hampton, Daniel Zinn, Karen Phaik Har Lim, Harshal Abhyankar, Brooks Scull, Vijetha Kumar, Nipun Kakkar, David A. Wheeler, Angshumoy Roy, Poulikos I. Poulikakos, Miriam Mérad, Kenneth L. McClain, D. Williams Parsons, Carl E. Allen

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldMedicine
TopicHistiocytic Disorders and Treatments
Canadian institutionsPediatric Oncology Group
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Human Genome Research InstitutePlexxikonNational Cancer InstituteNational Institutes of HealthLester and Sue Smith FoundationDan L. Duncan Cancer Center, Baylor College of MedicineHoward Hughes Medical InstituteSt. Baldrick's FoundationAlex's Lemonade Stand Foundation for Childhood Cancer
KeywordsMAPK/ERK pathwayLangerhans cell histiocytosisCancer researchFusion geneMutationV600EBiologyGeneMedicineGeneticsSignal transductionPathologyDisease

Abstract

fetched live from OpenAlex

cells from lesions. ERK activation was resistant to BRAF-V600E inhibition, but responsive to both a second-generation BRAF inhibitor and a MEK inhibitor. These results support an emerging model of universal ERK-activating genetic alterations driving pathogenesis in LCH. A personalized approach in which patient-specific alterations are identified may be necessary to maximize benefit from targeted therapies for patients with LCH.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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

Citations169
Published2016
Admission routes1
Has abstractyes

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