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Record W2099731960 · doi:10.1111/jsap.12349

Acoustic radiation force impulse elastography of the spleen in healthy dogs of different ages

2015· article· en· W2099731960 on OpenAlexaff
Marjury Cristina Maronezi, Marcus Antônio Rossi Feliciano, Leandro Zuccolotto Crivellenti, Ana Paula Rodrigues Simões, Pawel M. Bartlewski, Inderbir S. Gill, Júlio Carlos Canola, W. R. R. Vicente

Bibliographic record

VenueJournal of Small Animal Practice · 2015
Typearticle
Languageen
FieldMedicine
TopicUltrasound Imaging and Elastography
Canadian institutionsUniversity of Guelph
FundersUniversidade Estadual PaulistaFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsMedicineEchogenicityElastographySpleenUltrasonographyRadiologyUltrasoundNuclear medicinePathologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To determine the elastographic characteristics of splenic parenchyma in clinically healthy dogs of various ages in order to establish preliminary qualitative and quantitative standards/reference intervals for this technique. MATERIALS AND METHODS: Thirty three healthy dogs categorized as young, adult and elderly were used. Splenic echotexture, echogenicity, size and ages were assessed with B-mode ultrasonography. Using qualitative elastography, the spleen (head, body and tail) was examined for homogeneity and presence of deformities. Shear velocities in different splenic segments were then quantitatively evaluated. RESULTS: All splenic segments visualised with the B-mode ultrasonography appeared normal. Different splenic segments examined with qualitative elastography were free of any detectable malformations and the images appeared as homogeneous dark areas. The mean shear velocity values were 2 · 32 m/s for head, 2 · 16 m/s for body and 2 · 25 m/s for tail of the spleen (P = 0 · 40), and they did not vary between the different age groups (P > 0 · 05). CLINICAL SIGNIFICANCE: Quantitative and qualitative ARFI elastography of the spleen in clinically healthy dogs differing in age could be easily performed, and it may aid in the diagnosis and evaluation of splenic abnormalities routinely assessed in veterinary practice with B-mode ultrasonography.

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.

How this classification was reachedexpand

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)0.002
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 score0.182
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 integrity0.0000.001
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 head0.022
GPT teacher head0.293
Teacher spread0.271 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2015
Admission routes1
Has abstractyes

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