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Record W4403228429 · doi:10.1038/s41591-024-03286-y

Prediction of brain metastasis development with DNA methylation signatures

2024· article· en· W4403228429 on OpenAlexafffund
Jeffrey Zuccato, Yasin Mamatjan, Farshad Nassiri, Andrew Ajisebutu, Jeffrey Liu, Ammara Muazzam, Olivia Singh, Wen Zhang, Mathew Voisin, Shideh Mirhadi, Suganth Suppiah, Leanne Wybenga-Groot, Alireza Tajik, Craig D. Simpson, Olli Saarela, Ming‐Sound Tsao, Thomas Kislinger, Kenneth Aldape, Michael F. Moran, Vikas Patil, Gelareh Zadeh

Bibliographic record

VenueNature Medicine · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsPublic Health OntarioHospital for Sick ChildrenPrincess Margaret Cancer CentreToronto General HospitalUniversity Health NetworkUniversity of TorontoThompson Rivers University
FundersCanadian Cancer Society Research InstituteCanadian Institutes of Health ResearchNational Cancer InstituteU.S. Department of Health and Human ServicesNational Institutes of HealthGovernment of CanadaFondation Brain Canada
KeywordsDNA methylationComputational biologyMethylationBrain metastasisBiologyMetastasisDNANeuroscienceBioinformaticsCancer researchGeneticsCancerGeneGene expression

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

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

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 head0.012
GPT teacher head0.272
Teacher spread0.260 · 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 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

Citations42
Published2024
Admission routes2
Has abstractyes

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