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Record W2063510309 · doi:10.1002/oa.1111

CT and micro‐CT analysis of a case of Paget's disease (<i>osteitis deformans</i>) in the Grant skeletal collection

2009· article· en· W2063510309 on OpenAlexaff
Andrew Wade, David W. Holdsworth, Gregory J. Garvin

Bibliographic record

VenueInternational Journal of Osteoarchaeology · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsSt Joseph's Health CareWestern University
Fundersnot available
KeywordsRadiographyMedicineOsteologyDifferential diagnosisProjectional radiographyRadiologyPlain radiographyOsteitis DeformansComputed tomographyPaleopathologyConventional radiographyPhysical examinationDiseaseAnatomyPathologyPaget's disease of bone

Abstract

fetched live from OpenAlex

Abstract This paper presents a case study in which Paget's disease of bone is differentially diagnosed in an individual from the Grant skeletal collection using non‐destructive computed tomography (CT) and micro‐computed tomography (micro‐CT) analyses of the pubis, in addition to plain film radiography and macroscopic examination. In archaeological and modern osteological samples diagnosis frequently relies on macroscopic examination, plain film radiography and histological examination of bone samples. CT and micro‐CT modalities provide researchers with a non‐destructive view of the internal structure of bone unhampered by the superimposition that is characteristic of plain film radiographs. Given the importance of the increased cortical and trabecular thickness in the differential diagnosis of Paget's disease, these techniques are ideal means by which to non‐destructively examine culturally‐sensitive and scientifically‐valuable human remains for signs of Paget's disease of bone. Copyright © 2009 John Wiley &amp; Sons, Ltd.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.007
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.271
Teacher spread0.256 · 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 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

Citations17
Published2009
Admission routes1
Has abstractyes

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