Chronic maxillary sinusitis in palaeopathology: A review of methods
Bibliographic record
Abstract
OBJECTIVE: This study reviews the palaeopathological literature discussing maxillary sinusitis to examine current trends and issues within the study of this condition, and to make recommendations for future research in this area. MATERIALS: Seventy-five studies were identified through a literature search of digital and physical sources. METHODS: Information regarding study metadata, the populations investigated, sinusitis diagnostic criteria, and sinusitis prevalence was examined. RESULTS: Populations from the UK and Europe were the most studied, reflecting both palaeopathology's systemic colonialism and academic legacies. Most studies used diagnostic criteria published in the mid-1990s, with some subsequent studies modifying these criteria. CONCLUSIONS: The diagnostic criteria from 1995 are widely used but do not include all possible bone changes seen within sinusitis. There is also a need for researchers to engage in issues of data reductionism when using descriptive categories for archaeological sites and populations. SIGNIFICANCE: This paper provides considerations as to how the 1995 diagnostic criteria may be revised by future researchers and synthesises much of the published sinusitis prevalence data to assist researchers interested in the palaeopathology of respiratory disease. LIMITATIONS: More general osteological research, which includes palaeopathological information, was likely missed from this review due to the choice of key terms and languages used in the literature search. SUGGESTIONS FOR FURTHER RESEARCH: Additional research into sinusitis in archaeological populations outside of Western Europe is required. Further work examining the ability to compare pathological data from macroscopic observation and medical imaging would be advantageous to palaeopathology as a whole.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.015 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".