Bibliographic record
Abstract
Transesophageal echocardiography provides unique diagnostic capabilities, allowing for a very precise look at the structure and hemodynamics of the human heart. It is minimally invasive and portable, and quickly diagnoses sudden hemodynamic changes in intensive care patients. It provides invaluable and precise information about myocardial dysfunction and intracardiac volume status. It can diagnose dynamic left ventricular outflow obstruction, infrequent but serious complication of aortic valve replacement, septal myectomy, or mitral valve repair. Transesophageal echocardiography examination can exclude cardiac tamponade and intracardiac source of embolization, and it offers the ability to visualize native or prosthetic valves and assesses their function in the postoperative period. It is helpful in diagnosing endocarditis and the presence of intracardiac masses. In the diagnosis of blunt chest trauma, transesophageal echocardiography offers a fast and safe look at ascending and descending aorta and pericardial effusion, facilitating future decisions about patient management. In patients with postoperative hypoxia, it can exclude intracardiac shunt. Finally, in heart transplants or in managing patients with mechanical heart assist devices, transesophageal echocardiography is an invaluable tool in assessing progress of treatment and complications arising from the procedures. With the introduction of multiplane transesophageal echocardiography probes, technology, and experienced personnel, transesophageal echocardiography becomes the extension of the physical examination in the intensive care unit. This example is one of only a few whereby technology brings the physician closer to the patient.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.010 |
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".