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Record W2011420281 · doi:10.4161/cam.26728

Epithelial-mesenchymal transition and its regulators are major targets of triple-negative breast cancer

2013· article· en· W2011420281 on OpenAlexafffund
Ala‐Eddin Al Moustafa

Bibliographic record

VenueCell Adhesion & Migration · 2013
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsConcordia UniversityMcGill University
FundersCanadian Institutes of Health Research
KeywordsEpithelial–mesenchymal transitionTriple-negative breast cancerBreast cancerCancer researchMetastasisBreast cancer metastasisTransition (genetics)CancerOncologyMedicineInternal medicineBiologyCancer metastasisGene

Abstract

fetched live from OpenAlex

Triple negative breast cancers (TNBCs) represent a distinct subtype of breast cancers that are associated with early recurrence and an aggressive metastatic progression of the disease and consequently poor outcome. Recently, it was reported that c-Met growth factor receptor is overexpressed in around 52% of TNBCs. On the other hand, it is known that c-Met signaling pathways initiate the epithelial-mesenchymal transition (EMT) phenomenon, which is described as a crucial event during cancer metastasis. Herein, we discuss the association between c-Met and EMT in the TNBC group.

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: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.242
Teacher spread0.230 · 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 designObservational
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

Citations24
Published2013
Admission routes2
Has abstractyes

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