Possible environment influence in spine segmentation anomalies
Bibliographic record
Abstract
Segmentation anomalies of the spine transformations are relatively common in humans, mainly in adjacent regions. Its aetiology is multifactorial, a combination of genetic, environmental, and epigenetic interaction. A sample of 50 adult individuals of both sexes from two different sites and chronologies of the current Argentine territory was examined. This work proposes a new approach to analyse segmentation anomalies, considering the taphonomic characteristics of the spine, together with the most common occasional contour shifts of such anomalies. Likewise, a bibliographic review was conducted to compile the knowledge achieved to date on this topic. The results showed different patterns of expression of segmentation anomalies among the analysed samples, with the lumbosacral transformations being the most prevalent. The similarities and disparities observed between Southern Patagonian samples and Inuit populations suggest that cold, as an environmental factor, could play an important role in the phenotypic plasticity of human populations. Similarly, hypoxia could influence the sample from Pukará de Tilcara. Due to the scarce existing methodological standardization for addressing segmentation anomalies, a systematization of the methods used to analyse segmentation anomalies is recommended; our approach is a proposal for this purpose.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".