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Record W4367595762 · doi:10.29007/2qhl

An Association Analysis of Breast Cancer with Carotenoids.

2023· article· en· W4367595762 on OpenAlex

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

VenueEPiC series in computing · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsMacEwan UniversityUniversity of Alberta
Fundersnot available
KeywordsExposomeBreast cancerCancerMedicineCarcinogenesisOncologyBioinformaticsEnvironmental healthBiologyInternal medicine

Abstract

fetched live from OpenAlex

The environment and the exposure individuals carry throughout their lifetime can gar- ner diverse effects on their health. This paper discusses the application of association analysis, to determine relationships between carcinogenesis and the human exposome. Human exposome data from the World Health Organization was analyzed to determine associations between human exposure and breast cancer. The discovered associations outline specific factors that may be associated with the prevention or causation of breast cancer. We discovered an association between biomarkers in specific biospecimens and breast cancer. Xanthophylls, measured in two different biospecimens, were determined to be associated with American breast cancer patients. The associations discovered may be of use in future cancer studies. This research is particularly interesting because of xanthophylls’ relationship to retinol, inhibiting oncogenesis. Providing support and data for such associations will encourage more research on the exposome’s effect on breast cancer and other conditions.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

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

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 head0.006
GPT teacher head0.267
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