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Record W2725300137 · doi:10.12968/coan.2017.22.7.388

A general practitioner's guide to FAST cageside ultrasound techniques

2017· article· en· W2725300137 on OpenAlexaff
Ellen Milley, Søren Boysen, Jenefer R. Stillion

Bibliographic record

VenueCompanion animal · 2017
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsCalgary Laboratory ServicesUniversity of Calgary
Fundersnot available
KeywordsMedicinePneumothoraxTriageRadiologyUltrasoundFocused assessment with sonography for traumaMedical physicsAbdominal traumaMedical emergencyBlunt

Abstract

fetched live from OpenAlex

An overview of FAST (focused assessment with sonography for trauma, triage and tracking) is provided, including imaging techniques for both abdominal and thoracic FAST (AFAST and TFAST). This article serves as a practical guide for general and emergency room veterinary surgeons wanting to incorporate the ultrasound FAST scan into everyday practice. Indications for FAST scan, methodology and common pitfalls are reviewed, with the aim of making this diagnostic technique accessible to every practice with ultrasound capabilities. Rapid early detection of pneumothorax, and of peritoneal, pericardial and pleural effusions, allows for further appropriate patient-directed diagnostic evaluation and therapy.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.681
Threshold uncertainty score0.908

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.001

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 head0.049
GPT teacher head0.401
Teacher spread0.353 · 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 designBench or experimental
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

Citations2
Published2017
Admission routes1
Has abstractyes

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