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Record W2069171939 · doi:10.1097/cej.0b013e3283429e32

Salt, processed meat and the risk of cancer

2010· article· en· W2069171939 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

VenueEuropean Journal of Cancer Prevention · 2010
Typearticle
Languageen
FieldNursing
TopicSodium Intake and Health
Canadian institutionsPublic Health Agency of Canada
FundersAssociazione Italiana per la Ricerca sul CancroAmerican Institute for Cancer Research
KeywordsSalt (chemistry)MedicineProcessed meatCancerEnvironmental healthFood scienceInternal medicineChemistry

Abstract

fetched live from OpenAlex

This study assesses the association between salt added at the table, processed meat and the risk of various cancers. Mailed questionnaires were completed by 19 732 patients with histologically confirmed incident cancer of the stomach, colon, rectum, pancreas, lung, breast, ovary, prostate, testis, kidney, bladder, brain, non-Hodgkin's lymphoma or leukaemia, and 5039 population controls,between 1994 and 1997. Measurement included information on socioeconomic status, lifestyle habits and diet. A 69-item food frequency questionnaire provided data on eating habits 2 years before the study. Odds ratios and 95% confidence intervals were derived through unconditional logistic regression. Compared with never adding salt at the table, always or often adding salt at the table was associated with an increased risk of stomach, lung, testicular and bladder cancer. Processed meat was significantly related to the risk of the stomach, colon, rectum, pancreas, lung, prostate, testis, kidney and bladder cancer and leukaemia; the odds ratios for the highest quartile ranged from 1.3 to 1.7. The findings add to the evidence that high consumption of salt and processed meat may play a role in the aetiology of several cancers.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.793
Threshold uncertainty score0.200

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.016
GPT teacher head0.320
Teacher spread0.303 · 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