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Record W4205368928 · doi:10.4103/glioma.glioma_17_21

Pediatric posterior fossa ependymoma and metabolism

2021· article· en· W4205368928 on OpenAlexaff
Katharine Halligan, Andrea Cruz, James Felker, Craig Daniels, Michael D. Taylor, Sameer Agnihotri

Bibliographic record

VenueGlioma · 2021
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsEpendymomaCarcinogenesisBiologyMetabolismCancer researchTumor microenvironmentNeuroscienceBrain tumorCentral nervous systemCancer cellCancerTumor cellsBioinformaticsPathologyEndocrinologyMedicineGenetics

Abstract

fetched live from OpenAlex

Ependymomas are a lethal central nervous system (CNS) tumor found in both adults and children. Recent efforts have focused on risk stratification by classifying the molecular variants of CNS ependymoma. Despite this increased knowledge of molecular drivers, much less is known about the metabolism of these subgroups. Disruption of cellular metabolism can drive the transition of normal neuronal cells to tumor cells. A shift from anaerobic to aerobic metabolism as the primary energy source is a hallmark of cancer, promoting cancer cell proliferation, and avoidance of cellular apoptotic cues. This review aims to discuss the current knowledge regarding metabolism in ependymoma cells compared to normal brain cells and the implications of metabolic changes with regard to tumorigenesis, the tumor microenvironment, and possible targets for treatment.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.256
Teacher spread0.243 · 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 designBench or experimental
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

Citations1
Published2021
Admission routes1
Has abstractyes

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