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Record W2899883991 · doi:10.1093/neuonc/noy148.844

PDTM-02. STRESS GRANULES ARE INDUCED BY OXIDATIVE STRESS IN PEDIATRIC BRAIN TUMORS AND PREDICT POOR OUTCOME

2018· article· en· W2899883991 on OpenAlexaff
Alberto Delaidelli, Gian Luca Negri, Brian Cho, Sean W. Minaker, Amal M. El-Naggar, Juliette Hukin, Stephen Yip, Mariarita Santi, John M. Maris, Poul H. Sorensen

Bibliographic record

VenueNeuro-Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicThermal Regulation in Medicine
Canadian institutionsChildren's & Women's Health Centre of British ColumbiaUniversity of British Columbia
Fundersnot available
KeywordsOxidative stressImmunohistochemistryStress granuleRNA-binding proteinTissue microarrayCancer researchBiologyMedicinePediatric cancerPathologyInternal medicineCancerMessenger RNATranslation (biology)Gene

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.024
GPT teacher head0.322
Teacher spread0.298 · 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.

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

Citations1
Published2018
Admission routes1
Has abstractyes

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