Development and application of a food frequency questionnaire for use in breast cancer research in Prince Edward Island
Bibliographic record
Abstract
The primary purpose of this research was to develop and pilot test a population specific, semi-quantitative food frequency questionnaire (FFQ) for use in breast cancer research in Prince Edward Island (PEI). It was hypothesized that Island women recently diagnosed with breast cancer would have significantly lower intakes of n-3 fatty acids, monounsaturated fats, total dietary fibre and carotenoids than would women never diagnosed with breast cancer. The research was conducted in two phases. Phase I involved the development of the FFQ. In Phase II a pilot test of the FFQ was conducted in women with newly diagnosed breast cancer and women never diagnosed with breast cancer to: (a ) verify the performance of the questionnaire in regards to the food list length, contents and format; (b) assess dietary intakes of nutrients hypothesized to play a role in breast cancer incidence in cases and controls; (c) assess dietary adequacy; and (d) to investigate to the extent possible the association of dietary risk factors with breast cancer in recently diagnosed cases and controls in PEI.
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".