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Record W2291349339 · doi:10.1101/mcs.a000679

Molecular etiology of an indolent lymphoproliferative disorder determined by whole-genome sequencing

2016· article· en· W2291349339 on OpenAlexafffund
Jeremy Parker, Yaoqing Shen, Erin Pleasance, Yvonne Li, Jacqueline E. Schein, Yongjun Zhao, Richard A. Moore, Joanna Wegrzyn-Woltosz, Kerry J. Savage, Andrew P. Weng, Randy D. Gascoyne, Steven J.M. Jones, Marco A. Marra, Janessa Laskin, Aly Karsan

Bibliographic record

VenueMolecular Case Studies · 2016
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsTerry Fox Research InstituteBC Cancer AgencyCanada's Michael Smith Genome Sciences Centre
FundersTerry Fox FoundationMichael Smith Health Research BC
KeywordsChronic lymphocytic leukemiaGenomeLymphoproliferative disordersBiologyDNA sequencingTranscriptomeLymphomaGene expression profilingWhole genome sequencingGeneDigital polymerase chain reactionGeneticsCancer genome sequencingLeukemiaComputational biologyGene expressionPolymerase chain reactionImmunology

Abstract

fetched live from OpenAlex

In an attempt to assess potential treatment options, whole-genome and transcriptome sequencing were performed on a patient with an unclassifiable small lymphoproliferative disorder. Variants from genome sequencing were prioritized using a combination of comparative variant distributions in a spectrum of lymphomas, and meta-analyses of gene expression profiling. In this patient, the molecular variants that we believe to be most relevant to the disease presentation most strongly resemble a diffuse large B-cell lymphoma (DLBCL), whereas the gene expression data are most consistent with a low-grade chronic lymphocytic leukemia (CLL). The variant of greatest interest was a predicted NOTCH2-truncating mutation, which has been recently reported in various lymphomas.

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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.329
Teacher spread0.304 · 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 designCase report
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

Citations3
Published2016
Admission routes2
Has abstractyes

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