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Record W2080041412 · doi:10.1038/srep00227

A Gene Signature for Predicting Outcome in Patients with Basal-like Breast Cancer

2012· article· en· W2080041412 on OpenAlexafffund
Robin Hallett, Anna Dvorkin‐Gheva, Anita Bane, John A. Hassell

Bibliographic record

VenueScientific Reports · 2012
Typearticle
Languageen
FieldMedicine
TopicNonmelanoma Skin Cancer Studies
Canadian institutionsJuravinski Cancer CentreMcMaster UniversityMcMaster University Medical Centre
FundersStem Cell NetworkOntario Institute for Cancer Research
KeywordsBreast cancerBasal (medicine)OncologyMedicineInternal medicineDiseaseCancerGene signatureBioinformaticsGeneBiologyGene expressionGenetics

Abstract

fetched live from OpenAlex

Basal-like breast cancer is a molecular subtype of breast cancer with a poor prognosis. Follow-up studies of long-term outcome in these patients, demonstrates they can be separated into two clinical groups: those who succumb to their disease within the first 5 years and those expected to show excellent long term survival. Currently available clinical/histopathological variables as well as molecular signatures show little capacity to identify basal breast cancer patients with either a high or low risk of disease relapse. Using data derived from 85 basal-like breast cancer patients, we identified a 14-gene signature, which we subsequently validated on an additional 49 basal breast cancer patient set. The ability to distinguish between these two sub-groups of basal breast cancer patients at the time of initial diagnosis would permit tailoring aggressive therapeutic regimens to those patients with a poor prognosis and conversely avoid such therapy in low risk patients.

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)0.001
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.276
Teacher spread0.261 · 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

Citations120
Published2012
Admission routes2
Has abstractyes

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