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Time-Course Characterization of the Computed Tomography Contrast Enhancement of an Iodinated Blood-Pool Contrast Agent in Mice Using a Volumetric Flat-Panel Equipped Computed Tomography Scanner

2006· article· en· W2062436949 on OpenAlex
Nancy L. Ford, Kevin C. Graham, A. C. Groom, Ian C. MacDonald, Ann F. Chambers, David W. Holdsworth

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

VenueInvestigative Radiology · 2006
Typearticle
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsRobarts Clinical TrialsWestern University
Fundersnot available
KeywordsIodinated contrastContrast (vision)MedicineComputed tomographyNuclear medicineTomographyHounsfield scaleSpleenRadiologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this study was to determine the time-course of computed tomography (CT) contrast enhancement of an iodinated blood-pool contrast agent. METHODS: Five C57BL/6 mice were anesthetized, imaged at baseline, and given an iodinated blood-pool contrast agent. Micro-CT scans were acquired at 0, 0.25, 0.5, 1, 2, 4, 8, and 24 hours after injection. The mean CT number was determined in a region of interest in 7 organs. RESULTS: The CT contrast enhancement was plotted as a function of time for each organ. We identified an imaging window immediately after injection suitable for visualizing the vascular system and a second imaging window at 24 hours for visualizing liver and spleen. CONCLUSIONS: A single injection of the blood-pool contrast agent can be used for dual-phase investigations of the vasculature (t = 0 hours) and liver (t = 24 hours), which can be applied to studies of liver tumors or disease.

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 score0.167
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
Bibliometrics0.0010.002
Science and technology studies0.0000.001
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 head0.038
GPT teacher head0.239
Teacher spread0.201 · 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