Internipple distance and internipple index.
Bibliographic record
Abstract
OBJECTIVE: To determine the internipple distance and internipple index in Chinese children. METHODS: The internipple distance and chest circumference were measured in 3,290 healthy Chinese children (1,715 males and 1,575 females) aged birth to 18 years seen at the Asian Medical Centre. The internipple distance and chest circumference were obtained at the end of expiration whenever possible, with a standard nonstretch tape measure graduated in millimeters with the arms hanging relaxed alongside the body. Patients under two years of age were measured supine and those over two years of age standing. The internipple distance was measured between the centers of both nipples, and the chest circumference was measured across the internipple line. The internipple index was calculated according to the formula: internipple distance (cm) multiplied by 100 and divided by chest circumference (cm). RESULTS: The internipple distance and chest circumference increased with age. The internipple index was highest in the neonatal period (26.4 +/- 1.6 for males and 26.3 +/- 2 for females), and decreased steadily until the age of four years (23.8 +/- 1.2 for males and 23.8 +/- 1.4 for females), and thereafter was relatively constant through the age of 18 years in males and the age of 11 years in females. In females, the internipple index decreased gradually from the age of 11 years to 18 years. CONCLUSIONS: While internipple index is a more practical way to assess nipple placement, there are ethnic differences in the internipple index. Proper reference standards should be used in the assessment whether the nipples are closely or widely spaced.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".