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Record W2101976544 · doi:10.1186/1475-2867-5-10

Rel/Nuclear factor-kappa B apoptosis pathways in human cervical cancer cells

2005· article· en· W2101976544 on OpenAlexaff
Marlene Shehata

Bibliographic record

VenueCancer Cell International · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNF-κB Signaling Pathways
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCervical cancerMedicineApoptosisCancerCarcinogenesisCancer researchHeLaPathogenesisBioinformaticsImmunologyInternal medicineBiologyCellGenetics

Abstract

fetched live from OpenAlex

Cervical cancer is considered a common yet preventable cause of death in women. It has been estimated that about 420 women out of the 1400 women diagnosed with cervical cancer will die during 5 years from diagnosis. This review addresses the pathogenesis of cervical cancer in humans with a special emphasis on the human papilloma virus as a predominant cause of cervical cancer in humans. The current understanding of apoptosis and regulators of apoptosis as well as their implication in carcinogenesis will follow. A special focus will be given to the role of Rel/NF-kappaB family of genes in the growth and chemotherapeutic treatment of the malignant HeLa cervical cells emphasizing on Xrel3, a cRel homologue.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.019
GPT teacher head0.272
Teacher spread0.253 · 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

Citations20
Published2005
Admission routes1
Has abstractyes

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