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Record W2324664643 · doi:10.1097/rct.0b013e31826739f5

Computed Tomography (CT) Bone Segmentation of an Ancient Egyptian Mummy A Comparison of Automated and Semiautomated Threshold and Dual-Energy Techniques

2012· article· en· W2324664643 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Computer Assisted Tomography · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced X-ray and CT Imaging
Canadian institutionsOttawa HospitalLawson Health Research InstituteWestern University
Fundersnot available
KeywordsMedicineTomographyComputed tomographySegmentationDual energyNuclear medicineRadiologyArtificial intelligenceBone mineralOsteoporosisPathology

Abstract

fetched live from OpenAlex

Dual-energy computed tomography (CT) enables 3-dimensional,noninvasive, and nondestructive imaging with material separation. Dual-energy CT is generally used to segment hydrated tissues within the clinical context. We apply dual-energy CT to an ancient Egyptian mummy and present several techniques designed to separate bone from desiccated tissue and resin. Automated and semiautomated dual-energy CT techniques are compared to manual segmentation and thresholding-based techniques. Semiautomated techniques enable substantial reductions in operator time compared to manual segmentation.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.257
Teacher spread0.247 · 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