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Record W2961765034 · doi:10.3389/fvets.2019.00237

Traumatic Pulmonary Pseudocysts in a Young Dog Following Non-penetrating Blunt Thoracic Trauma

2019· article· en· W2961765034 on OpenAlexaboutno aff
Natosha Mulholland, Iain Keir

Bibliographic record

VenueFrontiers in Veterinary Science · 2019
Typearticle
Languageen
FieldMedicine
TopicTrauma Management and Diagnosis
Canadian institutionsnot available
Fundersnot available
KeywordsBluntMedicinePenetrating traumaThoracic traumaBlunt traumaSurgeryRadiology

Abstract

fetched live from OpenAlex

Traumatic pulmonary pseudocysts following non-penetrating blunt thoracic trauma is a well-described phenomenon in the human literature, while in veterinary medicine, this disease process is rarely reported and poorly described in the current literature available. This case report describes a 1.5-year-old male castrated Labrador retriever with findings of pulmonary cysts following a road traffic accident. The goal of this report is to expound upon the pathophysiology, diagnosis, and treatment of this disease process in the veterinary field.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.022
GPT teacher head0.310
Teacher spread0.288 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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