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Record W3080547630 · doi:10.1016/j.dib.2020.106229

Methylation data of mouse Rb-deficient pineoblastoma

2020· article· en· W3080547630 on OpenAlexafffund
Philip E.D. Chung, Eldad Zacksenhaus

Bibliographic record

VenueData in Brief · 2020
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsMethylationEpigeneticsDNA methylationBiologyBrain tumorCancer researchComputational biologyPathologyGeneticsMedicineGeneGene expression

Abstract

fetched live from OpenAlex

Methylation profiling is widely used to study tumor biology and perform cluster analysis, particularly in brain cancer research where tissue biopsies are scarce. We have recently reported on the development of novel mouse models for germ line mutations in pineoblastoma (Nature Communications, 2020). Here, we present unpublished methylation profiling of 8 Rb-deleted/p53-deleted pineoblastoma from our mouse model as well as 3 normal cerebellum tissues as control. The primary dataset can be accessed via SRA (PRJNA638504). These methylation data can be used to perform inter- and intra-species comparisons with other brain cancers as well as with specific subtypes of pineoblastoma, and to investigate potential epigenetic mechanisms and pathways underlying Rb-deficient pineoblastoma-genesis..

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: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.003

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 head0.117
GPT teacher head0.338
Teacher spread0.221 · 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
GenreDataset

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

Citations1
Published2020
Admission routes2
Has abstractyes

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