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Record W2789350718 · doi:10.1017/s1551929500057618

Novel Developments in High-frequency Micro-Ultrasound Imaging

2006· article· en· W2789350718 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

VenueMicroscopy Today · 2006
Typearticle
Languageen
FieldMedicine
TopicUltrasound Imaging and Elastography
Canadian institutionsFujiFilm VisualSonics (Canada)
Fundersnot available
KeywordsUltrasoundBlood flowMedicineBiomedical engineeringModality (human–computer interaction)Doppler imagingRadiologyUltrasound imagingMedical physicsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract With the mapping of the mouse genome, the growing sophistication in transgenic sciences creating complex mouse models of disease, and the demand to study disease in vivo, there has been a corresponding increase in the demand for and development of preclinical imaging modalities. Clinical ultrasound operating in the 2-12 MHz range is a well established clinical imaging modality, accounting for more than one-third of all imaging procedures performed in North America. The simplicity, ease of use, speed, and safety of ultrasound have led to its significant role in diagnosis, treatment assessment, follow-up, and guidance of therapy in clinical applications. Ultrasound imaging is used routinely in its B-Mode imaging mode to report on soft tissue structures. It's also used in its Doppler modes for the measurement of blood velocity in fast-flowing targets such as the cardiovascular system, in slow-flowing applications such as quantifying blood flow and in vascular architectures within tumors.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.396
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.246
Teacher spread0.240 · 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