Harris Lines as Indicators of Physiological Stress in the Middle Holocene Cis-Baikal
Bibliographic record
Abstract
This article is a plain language summary of a master’s thesis completed in 2022 through the Department of Archaeology and Anthropology at the University of Saskatchewan. The goal of this research was to study Harris lines (HL; transverse lines in human and animal long bones that are only visible through X-rays) in the skeletal remains of hunter-gatherers from the Middle Holocene (~9000–3000 years BP) Baikal region of the Russian Federation. HL have often been associated with stress events such as malnutrition or disease in early life. Thus, this thesis expected to highlight differences in the lived stress experiences of two distinct cultural periods from the region which had already been shown in previous studies on stress. Individuals 25 years and younger at time of death from two cemetery populations dating to the Early Neolithic (EN; 7560–6660 years BP) and one from the Late Neolithic (LN; 6060–4970 years BP) were examined for HL. The data was then compared between EN and LN individuals to determine if one population experienced greater stress than the other based on higher HL counts. This thesis demonstrated that HL are not irrefutably tied to stress in EN and LN populations from the Cis-Baikal and HL are not reliable determinants of how often or how many periods of stress they experienced during development. This thesis also challenged ongoing critiques in the study of HL, including image capture methods, to facilitate future research and discussion relating to HL.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".