Bibliographic record
Abstract
Cardiac thrombi often present as a homogenous echodensity on cardiac imaging that may be incidentally discovered. A thrombus must be differentiated from vegetations, tumors and normal variant anatomy as their treatments are different. Cardiac thrombi are often located in cardiac chambers, most commonly the left atrium and left atrial appendage, where there is more stagnant blood flow. Thrombi may also form in structurally altered cardiac chambers as well as seen in dilated cardiomyopathy and in ventricular aneurysms. Symptoms, if present, may vary from dyspnea, angina and compressive symptoms. Currently, transthoracic echocardiography, transesophageal echocardiography and magnetic resonance imaging (MRI) are the accepted modalities to evaluate cardiac masses. MRI has been used with more frequency due to its ability to delineate mass borders, determine endocardial involvement and in its ability to detect blood flow. Few cases have been described of a large cardiac thrombus extending through the valves to include multiple chambers. In our case presentation, we describe a 91-year-old female with no significant cardiac history who presented with a non-ST elevation myocardial infarction where a transthoracic echocardiogram revealed a large intracavitary thrombus. J Med Cases. 2016;7(7):303-306 doi: http://dx.doi.org/10.14740/jmc2553w
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".