Bibliographic record
Abstract
BACKGROUND: Despite the overwhelming advantages of breast-feeding, there is a persistent concern that maternal exposure to chemical contaminants may result in contamination of breast milk and have an effect on the child's growth and development. A parallel concern regarding lactation in women with silicone implants over the past years has led to confusion and anxiety relating to the potential risks to the child. METHODS: The author reviewed the facts and issues as he knows them, including biomaterials, lactation toxicology, and a previous study where no difference was found in silicon (a proxy measurement of silicone) in women breast-feeding with silicone implants and those without. RESULTS: In the author's previous study, he compared women with implants to women without implants as controls and showed that mean silicon levels were not significantly different in breast milk (55.45 +/- 35 and 51.05 +/- 31 ng/ml, respectively) or in blood (79.29 +/- 87 and 103.76 +/- 112 ng/ml, respectively). However, silicon levels in alternative methods of infant nutrition were much higher. The mean silicon level measured in store-bought cow's milk was 708.94 ng/ml, whereas that for 26 brands of commercially available infant formula was 4402.5 ng/ml. CONCLUSIONS: In this review, the author looked only at silicon/silicone and did not address other potential contaminants that may be associated with silicone gel or the elastomer shell. This report may provide plastic surgeons and other healthcare workers with information regarding silicon/silicone for discussion with women with gel implants who are contemplating breast-feeding.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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, 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".