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Record W2060211329 · doi:10.1200/jco.2008.17.6792

Brain Tumor Stem Cells: Bringing Order to the Chaos of Brain Cancer

2008· review· en· W2060211329 on OpenAlexaff
Peter B. Dirks

Bibliographic record

VenueJournal of Clinical Oncology · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsCancer stem cellStem cellNeuroscienceMedicineBrain cancerBrain tumorCancerCancer researchIn vivoBiologyBioinformaticsPathologyCell biologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

Brain tumors are generally incurable cancers. Work from a number of laboratories strongly suggests that they are organized as a hierarchy based on a subset of cancer cells that have stem-cell properties. These cells have now been shown to be resistant to conventional therapy and responsive to differentiation therapy. New in vitro and in vivo models for interrogating brain tumor cells in stem-cell conditions have been developed that provide important new opportunities for elucidating the key pathways responsible for driving the proliferation of these cells. Continued application of the principles of stem-cell biology to the study of brain cancers is likely to continue to bring further important insight into these aggressive cancers, bringing new treatments and understanding of the origins.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score0.665

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.150
GPT teacher head0.490
Teacher spread0.340 · 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 teacher head, 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

Citations170
Published2008
Admission routes1
Has abstractyes

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