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RADIOGRAPHIC DIAGNOSIS OF LUNG LOBE TORSION

2005· article· en· W2027088058 on OpenAlexaff
Marc‐André d’Anjou, Amy S. Tidwell, Silke Hecht

Bibliographic record

VenueVeterinary Radiology & Ultrasound · 2005
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineRadiographyMediastinal ShiftLungTorsion (gastropod)LobeCATSPleural effusionAnatomyRadiologyInternal medicine

Abstract

fetched live from OpenAlex

Clinical data, thoracic radiographs, ultrasonographic exams, and histopathologic reports in 13 dogs and two cats with confirmed lung lobe torsion were reviewed. Age of dogs ranged from 4 months to 11.5 years, (mean of 6.4 years) and several breeds of large and small dogs were represented. Right middle lobe torsion was predominant in large dogs (five of eight large breed dogs) and left cranial lobe torsion was more commonly seen in small dogs (three of five small-breed dogs). Two domestic short-hair cats, 10 and 14 years of age, had right cranial and right middle lobe torsion, respectively. Underlying thoracic disease was found in only five of 15 patients. On thoracic radiographs, increased lobar opacity and pleural effusion were found in all patients (100%). Small dispersed air bubbles were found within the affected lobe of 13 patients (87%). This pattern, which was the result of vesicular emphysema, was variably extensive, and became more evident on follow-up radiographs in five of six dogs. The lobar bronchi could be seen in only eight of 15 patients (54%), and appeared irregular, focally narrowed or blunted in six of the eight patients, and displaced in five of the eight. Other common radiographic findings included mediastinal shift (nine), curved and dorsally displaced trachea (seven), and axial rotation of the carina (seven). Ultrasonography was used in seven patients and considered generally useful, although variable signs were observed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.033
GPT teacher head0.340
Teacher spread0.307 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations59
Published2005
Admission routes1
Has abstractyes

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