Maxillary sinusitis as an indicator of respiratory health in past populations
Bibliographic record
Abstract
Chronic infectious respiratory disease in a past human population is investigated through the quantification of maxillary sinusitis among Iroquoian horticulturists. Three hundred forty-eight right and left maxillae of a Southern Ontario Iroquoian skeletal sample, Uxbridge Ossuary, ca. AD 1440, were examined for evidence of chronic infection (minimum number of individuals = 207: 114 adults, 22 adolescents, 38 juveniles and 33 infants). Modern clinical criteria were applied to differentiate lesions of respiratory and dental origin. Osseous lesions of the maxillary sinuses were observed in 50% of the individuals examined. These lesions are morphologically consistent with nonspecific lesions observed in other past populations that have been attributed to the presence of pathogens. The prevalence of maxillary sinusitis increases with age. Osseous changes suggestive of maxillary sinusitis of respiratory origin are at a maximum prevalence in juveniles and adolescents. In adults, infection of dental origin becomes a confounding factor in the identification of sinusitis of respiratory origin. Fifteenth century Iroquoians were experiencing high airborne pathogen levels and poor indoor air quality. The prevalence of maxillary sinusitis and the exploration of the origin of tissue injury may contribute to our reconstruction of the quality of life and the respiratory health status of past human populations.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".