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Record W2013254402 · doi:10.3390/ijms15011315

Molecular Basis of Cardiac Myxomas

2014· review· en· W2013254402 on OpenAlexaff
Pooja Singhal, Adriana Luk, Vivek Rao, Jagdish Butany

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2014
Typereview
Languageen
FieldMedicine
TopicCardiac tumors and thrombi
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineIntracardiac injectionCardiac TumorsAsymptomaticMyxomaRadiologyConstitutional symptomsEmbolismMagnetic resonance imagingInternal medicine

Abstract

fetched live from OpenAlex

Cardiac tumors are rare, and of these, primary cardiac tumors are even rarer. Metastatic cardiac tumors are about 100 times more common than the primary tumors. About 90% of primary cardiac tumors are benign, and of these the most common are cardiac myxomas. Approximately 12% of primary cardiac tumors are completely asymptomatic while others present with one or more signs and symptoms of the classical triad of hemodynamic changes due to intracardiac obstruction, embolism and nonspecific constitutional symptoms. Echocardiography is highly sensitive and specific in detecting cardiac tumors. Other helpful investigations are chest X-rays, magnetic resonance imaging and computerized tomography scan. Surgical excision is the treatment of choice for primary cardiac tumors and is usually associated with a good prognosis. This review article will focus on the general features of benign cardiac tumors with an emphasis on cardiac myxomas and their molecular basis.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.025
GPT teacher head0.360
Teacher spread0.335 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations56
Published2014
Admission routes1
Has abstractyes

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