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Record W2155487288 · doi:10.1016/s1470-2045(09)70187-1

TP53 codon 72 polymorphism and cervical cancer: a pooled analysis of individual data from 49 studies

2009· article· en· W2155487288 on OpenAlexaff
Stefanie J. Klug, Meike Ressing, Jochem Koenig, Martı́n C. Abba, Θεόδωρος Αγοραστός, S. Brenna, Marco Ciotti, BR Das, Annarosa Del Mistro, Aleksandra Dybikowska, Anna R. Giuliano, Živilė Gudlevičienė, Ulf Gyllensten, Andrea L. Fuessel Haws, Åslaug Helland, C. Simon Herrington, A. Hildesheim, Olivier Humbey, Sun Ha Jee, Jae‐Weon Kim, Margaret M. Madeleine, Joseph Menczer, Hys Ngan, Akira Nishikawa, Yoshimitsu Niwa, R.J. Pegoraro, M. Radhakrishna Pillai, Guglielmina Nadia Ranzani, G Rezza, Adam N. Rosenthal, Susanta Roychoudhury, Dhananjaya Saranath, Virgínia Minghelli Schmitt, Sharmila Sengupta, Wannapa Settheetham‐Ishida, Hiroshi Shirasawa, Peter J.F. Snijders, Mark H. Stoler, Angel Suarez-Rincon, Krisztina Szarka, Ruth Tachezy, Masatsugu Ueda, Ate GJ van der Zee, Magnus von Knebel Doeberitz, Ming‐Tsang Wu, Tsuyoshi Yamashita, Ingeborg Zehbe, Maria Blettner

Bibliographic record

VenueThe Lancet Oncology · 2009
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsThunder Bay Regional Research Institute
FundersNational Cancer InstituteDeutsche Forschungsgemeinschaft
KeywordsGenotypeHeterozygote advantageCervical cancerAlleleOdds ratioArginineGeneticsBiologyGenetic epidemiologyEpidemiologyAllele frequencyInternal medicineCancerMedicineGene

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.012
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.992
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.020
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0080.019
Bibliometrics0.0050.008
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.129
GPT teacher head0.399
Teacher spread0.270 · 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.

Study designMeta-analysis
DomainMethods
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

Citations158
Published2009
Admission routes1
Has abstractno

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