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Record W4368346938 · doi:10.47888/bne-1603

Two cases of concha bullosa in a contemporary Cypriot skeletal collection

2023· article· en· W4368346938 on OpenAlexaff
Stephen D. Haines, Stacy Hackner, Phillip McCheyne, Myeashea Alexander, Xenia-Paula Kyriakou

Bibliographic record

VenueBioarchaeology of the Near East · 2023
Typearticle
Languageen
FieldMedicine
TopicSinusitis and nasal conditions
Canadian institutionsAthabasca University
FundersCoastal Response Research Center, University of New Hampshire
KeywordsConcha bullosaSinusitisMedicineEtiologyDermatologyAnatomyPathologySurgery

Abstract

fetched live from OpenAlex

Concha bullosa is the hypertrophy of the superior, middle, or inferior nasal conchae, most commonly referring to the pneumatisation of the middle conchae. It is considered to be the most common anatomical variant of the osteomeatal complex, rather than a pathological development. Though it is common, its aetiology is poorly understood. It is unclear whether sex or ethnicity impacts on the prevalence of concha bullosa, though some research suggests a correlation. Some researchers have argued that concha bullosa predisposes individuals to sinusitis, but the link is not consistent. In this paper, the authors present two new skeletal cases of bilateral concha bullosa identified in female individuals taken from the Cyprus Reference Research Collection (CRRC). This work aims to highlight the limitations associated with the palaeopathological diagnosis of inflammation and the interpretation of skeletal lesions that may be related to sinusitis or infection of the osteomeatal complex in archaeological bone, in relation to the presence of concha bullosa.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0030.003
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.050
GPT teacher head0.312
Teacher spread0.263 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2023
Admission routes1
Has abstractyes

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