Lactation and breast cancer risk: a case–control study in Connecticut
Bibliographic record
Abstract
In this report, we examined the relationship between lactation and breast cancer risk, in a case-control study of breast cancer, conducted in Connecticut between 1994 and 1998. Included were 608 incident breast cancer cases and 609 age frequency matched controls, aged 30-80 years old. Cases and controls were interviewed by trained study interviewers, using a standardized, structured questionnaire, to obtain information on lactation and other major risk factors. Parous women who reported ever lactation had a borderline significantly reduced risk of breast cancer (OR = 0.83, 95% CI, 0.63-1.09). An OR of 0.53 (95% CI, 0.27-1.04) was observed in those having breastfed more than 3 children compared to those who never lactated. Women having breastfed their first child for more than 13 months had an OR of 0.47 (95% CI, 0.23-0.94) compared to those who never breastfed. Lifetime duration of lactation also showed a risk reduction while none of the ORs were statistically significant. Further stratification by menopausal status showed a risk reduction related to lactation for both pre- and postmenopausal women, while the relationship is less consistent for the latter. These results support an inverse association between breastfeeding and breast cancer risk.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".