Metadata record for the article: Treatment-related amenorrhea in a modern, prospective cohort study of young women with breast cancer
Bibliographic record
Abstract
Summary This metadata record provides details of the data supporting the claims of the related article: “Treatment-related amenorrhea in a modern, prospective cohort study of young women with breast cancer”. The related study evaluated factors associated with treatment-related amenorrhea (TRA) using logistic regression. Type of data: clinical data Subject of data: Homo sapiens Population characteristics: women diagnosed with breast cancer at age ≤40 Recruitment: Participants were enrolled from 12 sites in the United States and Canada from 2006-2016 within six months of diagnosis. Those who were able to respond to questionnaires in English were eligible. Trial registration number: NCT01468246 Data access The final analyses for the related study are contained in the 52 .csv files listed in the attached file ‘underlying_data_files_list.csv’. These files are not publicly available as the IRB-approved research protocol specified that all data must collected, coded, and stored at the Dana-Farber Cancer Institute and be limited-access and password-protected in the Partners system, in order to protect the identity of respondents. Requests can be made to share data privately. However, any data sharing will require a formal data transfer agreement between the Dana-Farber Cancer Institute and the other party. Requests to this effect should be directed to the corresponding author. Corresponding author(s) for this study Ann H. Partridge, MD, MPH, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215. Telephone: 617-632-3800. Fax: 617-632-1930. Email: ann_partridge@dfci.harvard.edu Study approval IRB approval for the study was obtained through Dana-Farber/Harvard Cancer Center (DF/HCC) and other participating centres.
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 | 0.007 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.723 | 0.175 |
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".