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Record W1972228943 · doi:10.1024/0036-7281.a000018

Echocardiographic findings in a goat with cor pulmonale secondary to chronic parasitic pneumonia

2010· article· de· W1972228943 on OpenAlexaff
Sébastien Buczinski, J.-M. Pinard, C. Ferrouillet, Maxime Veillette

Bibliographic record

VenueSchweizer Archiv für Tierheilkunde · 2010
Typearticle
Languagede
FieldMedicine
TopicCardiovascular Conditions and Treatments
Canadian institutionsCegep de Saint HyacintheUniversité de Montréal
Fundersnot available
KeywordsMedicineHeart failurePneumoniaAnorexiaCardiologyPulmonary heart diseaseAscitesInternal medicine

Abstract

fetched live from OpenAlex

Eine 4-jährige Ziege wurde eine Woche nach dem Ablammen wegen Apathie und Anorexie vorgestellt. Die klinische Untersuchung ergab Dyspnoe, einen hochgradigen Aszites und gestaute Jugularvenen, was für eine rechtsseitige kardiale Stauungsinsuffizienz sprach. Echokardiographisch konnte gestützt auf hochgradiger rechtsventrikulärer und rechtsatrialer Dilatation ein rechtsseitiges Herzversagen bestätigt werden. Nachdem keine Abnormalität im rechtsventrikulären Ausflusstrakt vorlag, wurde für diese Herzveränderungen im Zusammenhang mit der respiratorischen Symptomatik die Verdachtsdiagnose eines Cor pulmonale als Folge einer Lungenerkrankung gestellt. Aufgrund der schlechten Prognose wurde die Ziege euthanasiert. Die Autopsie ergab eine parasitäre Pneumonie und bestätigte den Verdacht eines sekundären Cor pulmonale. Die Echokardiographie ist ein interessantes Werkzeug, welches auch bei Ziegen im Stall für die kardiale Diagnostik eingesetzt werden kann, damit bei Fällen mit schlechter Prognose keine unnötigen Behandlungsversuche unternommen werden.

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)0.002
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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.250
Teacher spread0.244 · 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

Citations7
Published2010
Admission routes1
Has abstractyes

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