Recommendations for reporting perioperative transoesophageal echo studies
Bibliographic record
Abstract
Every perioperative transoesophageal echo (TEE) study should generate a written report. A verbal report may be given at the time of the study. Important findings must be included in the written report. Where the perioperative TEE findings are new, or have led to a change in operative surgery, postoperative care or in prognosis, it is essential that this information should be reported in writing and available as soon as possible after surgery. The ultrasound technology and methodology used to assess valve pathology, ventricular performance and any other derived information should be included to support any conclusions. This is particularly important in the case of new or unexpected findings. Particular attention should be attached to the echo findings following the completion of surgery. Every written report should include a written conclusion, which should be comprehensible to physicians who are not experts in echocardiography.
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 | 0.114 | 0.413 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.016 | 0.010 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.016 | 0.022 |
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".