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Record W4281662564 · doi:10.53785/2769-2779.1093

A Rare Presentation of Pericardial Tumor Presenting as Chronic Cough

2022· article· en· W4281662564 on OpenAlexaff
Swarup Sharma Rijal, William H. Risher, Aakankshya Kharel, Upendra Kaphle

Bibliographic record

VenueAdvances in Clinical Medical Research and Healthcare Delivery · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac tumors and thrombi
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChronic coughMedicineEtiologyAirwayPresentation (obstetrics)Rare diseaseSurgeryDiseaseDermatologyPathologyInternal medicineAsthma

Abstract

fetched live from OpenAlex

Chronic cough can pose various diagnostic and therapeutic dilemmas to physicians. Airway narrowing secondary to endoluminal disease or extrinsic compression are known etiologies of chronic cough. We report an extremely rare case of chronic cough due to extrinsic airway compression by a large pericardial lipoma with subsequent resolution of symptoms after the resection of the mass. This case provides insight into the rare etiology of chronic cough that is addressable with surgical intervention.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0040.002
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 head0.099
GPT teacher head0.524
Teacher spread0.425 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueAdvances in Clinical Medical Research and Healthcare DeliverySame topicCardiac tumors and thrombiFrench-language works237,207