MétaCan
Menu
Back to cohort
Record W2398072578 · doi:10.1097/rct.0000000000000442

Dual-Energy CT Characteristics of Parathyroid Adenomas on 25-and 55-Second 4D-CT Acquisitions

2016· article· en· W2398072578 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 · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced X-ray and CT Imaging
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsMedicineParathyroid adenomaNuclear medicineRadiologyAdenomaInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this study was to compare the dual-energy computed tomography (CT) characteristics of parathyroid adenomas (PAs), thyroid tissue, and lymph nodes (LNs) and assess whether the spectral information can improve distinction of these tissues. METHODS: Dual-energy CT scans from 20 patients with pathologically proven PAs were retrospectively evaluated, identifying 19 eligible PAs and region of interest analysis used for spectral characterization. RESULTS: There was a significant difference in multiple spectral parameters between PAs, LNs, and the thyroid gland (P < 0.05-0.0001). The greatest difference in spectral characteristics of PAs compared with that of LNs was on the 25-second acquisition, whereas the 55-second acquisition was better for distinguishing PAs from the thyroid gland. CONCLUSIONS: Four-dimensional CT acquired in dual-energy CT mode has the potential to further enhance diagnostic accuracy for PA identification on individual phases of the perfusion study.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.809
Threshold uncertainty score0.652

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.006
GPT teacher head0.201
Teacher spread0.195 · 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