Metadata record for the published article: Association between BMI, vitamin D, and estrogen levels in postmenopausal women using adjuvant letrozole: A prospective study
Bibliographic record
Abstract
<b>Summary</b>The data described in this metadata record underlie the figures, tables and supplementary files in the related manuscript: “Association between BMI, vitamin D, and estrogen levels in postmenopausal women using adjuvant letrozole: A prospective study”.<b>Data access</b>The data supporting the related manuscript are kept in institutional file storage on an internal server at Lunenfeld-Tanenbaum Research Institute. There are de-identification concerns in small, regionally restricted, clinical datasets which prevent these data being openly available, but data will be made available at reasonable request from the corresponding author for up to and including 5 years from publication of the related manuscript. For all data requests please contact: Dr David Cescon, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada. Dave.Cescon@uhn.ca<b>Data description</b>The data were gathered while investigating whether high BMI or 25-OH vitamin D levels were associated with higher estrogen levels in post-menopausal women receiving adjuvant letrozole, and while evaluating whether an increased dose of letrozole resulted in lower serum estrogens in women with BMI > 25 kg/m2.The following three files underlie all figures, tables and supplementary files of the related manuscript: alateststatus.txt, abase.txt, alabswide.txt.<b>Ethics</b>The associated trial is registered at ClinicalTrials.gov NCT01669343. The study was approved by the Ontario Research Ethics Board (OCREB), as well as each participating centre. Use of the letrozole 5 mg dose was authorized by a Health Canada Clinical Trial Application.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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 teacher head, 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".