ORIGINAL ARTICLE: Predictors of Inflammatory Breast Diseases During Lactation – Results of a Cohort Study
Bibliographic record
Abstract
PROBLEM: Inflammatory breast diseases during lactation are major reasons for early weaning. METHOD OF STUDY: A prospective cohort study was performed to examine the association between stress and inflammatory breast diseases. Psychometric data, cytokine levels in breast milk and blood samples were analysed postpartum (T1). Psychometric data and course of breast feeding were evaluated twelve weeks later (T2). Patients were divided into case- and control-groups (according to the presence of breast diseases). RESULTS: Mothers of the case group (n = 23) were significantly older and showed significantly increased stress levels between T1 and T2 compared with the control group (n = 43). Leucocytes in the postpartum blood count were significantly decreased in the case group. There were no significant differences between groups in the concentrations of Th-1- and Th-2-cytokines in breast milk postpartum. CONCLUSION: Higher maternal age, postpartum increase in stress perception and low number of leucocytes are associated with a higher incidence of inflammatory breast diseases. Further studies must examine the causality of this effect.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".