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Record W2130578918 · doi:10.1158/1055-9965.epi-03-0178

High-Throughput Detection of Glutathione <b> <i>S</i> </b>-Transferase Polymorphic Alleles in a Pediatric Cancer Population

2004· article· en· W2130578918 on OpenAlex
Phillip Barnette, R. Walther Schöll, Mary Blandford, L. Ballard, Alexander Tsodikov, Jalene Magee, Susana Williams, Margaret Robertson, Francis Ali‐Osman, Richard S. Lemons, Charles Keller

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlutathione Transferases and Polymorphisms
Canadian institutionsPediatric Oncology Group
FundersNIH Clinical CenterNational Center for Research ResourcesUniversity of Utah
KeywordsGenotypingGlutathione S-transferaseBiologyAlleleMolecular biologyGenotypePopulationCancerGeneticsCancer researchGlutathioneMedicineGeneEnzymeBiochemistry

Abstract

fetched live from OpenAlex

Polymorphisms of glutathione S-transferase (GST) enzymes have been correlated with altered risk of several cancers, as well as altered response and toxicity from cancer chemotherapy. We report a low cost, highly reproducible and specific PCR-based high-throughput assay for genotyping different GSTs designed for use in large clinical trials. In comparison to an alternative genotyping method (single nucleotide extension), the sensitivity and specificity of the high throughput assay was shown to be 92 and 97%, respectively, depending on the source of genomic DNA. Using the high-throughput assay, we demonstrate by multivariate analysis an increased risk of acute lymphoblastic leukemia, glial brain tumors, and osteosarcoma for patients carrying nonnull alleles of GSTM1 and/or GSTT1.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.501
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.020
GPT teacher head0.305
Teacher spread0.285 · 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