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High-Resolution Computed Tomography of Temporal Bone

2006· article· en· W4300877976 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 · 2006
Typearticle
Languageen
FieldMedicine
TopicEar Surgery and Otitis Media
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineComputed tomographyTemporal boneTomographyResolution (logic)Nuclear medicineHigh-resolution computed tomographyRadiologyAnatomyArtificial intelligence

Abstract

fetched live from OpenAlex

The purpose of this 4-part series is to illustrate the nuances of temporal bone anatomy using a high-resolution (200 μ isotropic) prototype volume computed tomography (CT) scanner. The normal anatomy in axial and coronal sections is depicted in the first and second parts. In this, the fourth part, and the third part, the structures that are removed and/or altered in 9 different surgical procedures are color coded and inscribed in the same coronal (article IV) and axial (article III) sections. The text stresses clinically important imaging features, including the normal postoperative appearance, and common complications after these operations. The superior resolution of the volume CT images is vital to the comprehensive and accurate representation of these operations. Minuscule intricate structures that are currently only localized in the mind's eye because of the resolution limit of conventional CT are clearly seen on these scans. This enhanced visualization, together with the information presented in the text, should assist in interpreting temporal bone scans, communicating with surgeons, and teaching this complex anatomy.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.823

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
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 head0.010
GPT teacher head0.224
Teacher spread0.214 · 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