INFECTIOUS DISEASE AS AN INDICATOR OF PHYSIOLOGICAL STRESS IN THE MIDDLE HOLOCENE CIS-BAIKAL
Bibliographic record
Abstract
Two distinct hunter-fisher-gatherer cultures lived on either side of a Middle Neolithic (or MN; 7,000/6,800-6,000/5,800 B.P.) archaeological hiatus in the Cis-Baikal, Siberia, Russian Federation.The Kitoi occupied the region in the Early Neolithic (or EN; 8,000-7,000/6,800 B.P.) and the Isakovo-Serovo-Glazkovo (or ISG) occupied the region in the Late Neolithic (or LN; 6,000/5,800-5,200 B.P.) into the Early Bronze Age (or EBA; 5,200/5,000-3,400 B.P.; Weber et al. 2015).Both of these cultures buried their dead in formal cemeteries located adjacent to the shores of Lake Baikal and along the many rivers of the Cis-Baikal.Research concerning the levels of physiological stress in the two cultures has found that the Kitoi suffered from more frequent and severe episodes of physiological stress than did the ISG (Lieverse et al. 2007a;Link 1999;Temple et al. 2014;Waters-Rist 2011;Waters-Rist et al. 2011).A detailed non-destructive visual examination of the osteological remains of 250 hunterfisher-gatherers from three cemeteries (Shamanka II, Lokomotiv, and Ust'-Ida I) from the middle Holocene Cis-Baikal was carried out to determine if non-specific infection-induced lesions occurred significantly more in those populations who were found to have been the most physiological stressed.An endoscope was used to examine individuals' middle ears and those sinuses that were unobservable to the human eye and were accessible through cracks in the skull; and a hand-held x-ray system was used to image individuals' mastoid processes.One question was asked of the presence/absence data: is the incidence of infection-induced lesions within the sample related to a) the type of infection, b) the sex of the individual, c) the age of the individual, d) the cemetery the individual came from, and/or e) the time period the individual lived in?To answer this question, binomial tests, chi-square tests, and generalized linear model logistic regression tests were conducted.These revealed the presence of statistically more lesions indicative of chronic non-specific infection in EN individuals, more specifically, in those from the cemetery of Lokomotiv, in males, and in those older than 20 years.It was concluded that non-specific infection-induced lesions occurred more in those populations who were found to have been the most physiological stressed.This study is in line with our understanding of stress, provides a much more detailed view into the community health of the Kitoi and the ISG than was previously known, and explores the lifeways of these two cultures through a new lens.SSHRC), the Northern Scientific Training Program of Canada (or NSTP), and the University of Saskatchewan.Second, I would like to thank my supervisor, Dr. Angela Lieverse, and the rest of my supervisory committee, Dr. Ernest Walker and Dr. David Cooper, who provided essential guidance, insight, and scrutiny throughout this research process.Thank you for keeping me focused, for motivating me when I needed it, and for saying, "you are the expert, so what do you think?"Those words gave me a sense of pride in my work and drove me to look deeper.Third, I would like to thank Dr. Eric Lamb, who allowed me to pepper him with statistics questions long after my statistics class with him was over.He now knows arguably more about palaeopathology than any other plant scientist at the university.Fourth, I would like to thank the Baikal-Hokkaido Archaeology Project (or BHAP) for allowing me to become a part of their team.As a new researcher, I have learned a lot about collaborative investigation through their willingness to share with me.I have been inspired to keep working within the field of paleopathology and with people like you.Fifth, I would like to thank two people from the department who have been nothing but supportive and incouraging since I have been at the university: Dr. Christopher Foley and Deborah Croteau.Thank you for the long talks and words of wisdom over the years.Sixth, and not least, I would like to thank my fiancé, parents, brother, other family, and friends who supported me through the highs and lows of research, and who were there for me every step of the way: thank you and I love you all.To my grandpa whose pride
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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".