Ecological factors and anthropometric morphological parameters of modern female population
Bibliographic record
Abstract
We have previously shown that ecological factors markedly change modern female body proportions. In this study we investigated the role of internal vs. external factors on the maturation and physiological functions of accelerated female population. We monitored main physiological parameters (EKG, blood pressure, respiratory parameters etc.) vs. bone length and muscle plasticity of 410 healthy female individuals at the age 20–27 and 520‐ at the age 17–19. Our results demonstrated that anthropological features and functional stability as well as body proportion of modern female population were genetically inherited from their mothers. Early maturation at 9.5–11 years revealed significant changes in height weight and plasticity but not in physiological parameters (p<0.05). Late maturation‐15–17 years, controversy, defined lower height and inadequate weight that could be considered as lack of environmental adaptation and inadequate physical activity and protein content in food supply. Sports training could partly compensate immature functions. In both groups subjects with scoliosis demonstrated lower physiological parameters (Student t‐test <0.05). Level of poverty, chronic diseases and ecological pollution of places of living and studying has the impact on maturation and time set of menarche (p<0.05). Conclusions Height, weight and late maturation could serve as markers for physiological functions alteration. [CIHR and NIH].
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".