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Record W4390205015 · doi:10.1016/j.ijpp.2023.11.005

Chronic maxillary sinusitis in palaeopathology: A review of methods

2023· review· en· W4390205015 on OpenAlexaff
Matthew J. Lee, Thomas Siek, Cara S. Hirst

Bibliographic record

VenueInternational Journal of Paleopathology · 2023
Typereview
Languageen
FieldMedicine
TopicSinusitis and nasal conditions
Canadian institutionsMcMaster University
FundersDurham University
KeywordsPaleopathologySinusitisMedicinePathologySurgery

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.920
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.113
GPT teacher head0.514
Teacher spread0.402 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations14
Published2023
Admission routes1
Has abstractyes

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