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Record W1964783858 · doi:10.1002/ijc.11327

Dietary risk factors for testicular carcinoma

2003· article· en· W1964783858 on OpenAlexaffabout
Michael J. Garner, Nicholas Birkett, Kenneth C. Johnson, Bryna Shatenstein, Parviz Ghadirian, Daniel Krewski

Bibliographic record

VenueInternational Journal of Cancer · 2003
Typearticle
Languageen
FieldMedicine
TopicTesticular diseases and treatments
Canadian institutionsUniversité de MontréalHealth CanadaInstitut Universitaire de Gériatrie de MontréalInstitute of Population and Public HealthUniversity of OttawaNatural Sciences and Engineering Research Council of Canada
Fundersnot available
KeywordsTesticular cancerOdds ratioMedicineConfidence intervalCancerPopulationPhysiologyGynecologyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Although testicular cancer is a relatively rare lesion, accounting for only 1.1% of all malignant neoplasms in males in Canada, it is the most common cancer among Canadian men 20-45 years of age. Knowledge of the causes of testicular cancer risk in general, and more specifically, its association with diet, remain limited. Data from 601 cases of testicular cancer and 744 population-based controls collected in 8 of the 10 Canadian provinces between 1994-97 were used to explore the relationship between diet and testicular cancer risk. We systematically examined 17 food groups, 15 nutrients and 4 individual foods based on data collected through a 69-item food-frequency questionnaire. Our results suggest that high dairy product intake, in particular high intake of cheese (odds ratio [OR] = 1.87; 95% confidence interval [CI] 1.22-2.86; p-trend < 0.001), is associated with an elevated risk of testicular cancer in Canadian males.

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 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 score0.015
Threshold uncertainty score0.212

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.024
GPT teacher head0.340
Teacher spread0.316 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations66
Published2003
Admission routes2
Has abstractyes

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