Upper limb musculoskeletal stress markers among middle Holocene foragers of Siberia's Cis‐Baikal region
Bibliographic record
Abstract
This evaluation of musculoskeletal stress markers (MSMs) in the Cis-Baikal focuses on upper limb activity reconstruction among the region's middle Holocene foragers, particularly as it pertains to adaptation and cultural change. The five cemetery populations investigated represent two discrete groups separated by an 800-1,000 year hiatus: the Early Neolithic (8000-7000/6800 cal. BP) Kitoi culture and the Late Neolithic/Bronze Age (6000/5800-4000 cal. BP) Isakovo-Serovo-Glaskovo (ISG) cultural complex. Twenty-four upper limb MSMs are investigated not only to gain a better understanding of activity throughout the middle Holocene, but also to independently assess the relative distinctiveness of Kitoi and ISG adaptive regimes. Results reveal higher heterogeneity in overall activity levels among Early Neolithic populations-with Kitoi males exhibiting more pronounced upper limb MSMs than both contemporary females and ISG males-but relative constancy during the Late Neolithic/Bronze Age, regardless of sex or possible status. On the other hand, activity patterns seem to have varied more during the latter period, with the supinator being ranked high among the ISG, but not the Kitoi, and forearm flexors and extensors being ranked generally low only among ISG females. Upper limb rank patterning does not distinguish Early Neolithic males, suggesting that their higher MSM scores reflect differences in the degree (intensity and/or duration), rather than the type, of activity employed. Finally, for both Kitoi and ISG peoples, activity patterns-especially the consistently high-ranked costoclavicular ligament and deltoid and pectoralis major muscles-appear to be consistent with watercraft use.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".