Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE OF REVIEW: The number of patients listed for lung transplantation largely exceeds the number of available transplantable organs because of both a shortage of organ donors and a low utilization rate of lungs from those donors. Two major innovations in recent years include the use of lungs from donations after cardiac death (DCD) and the use of ex-vivo lung perfusion (EVLP) to assess and improve injured donor lungs. RECENT FINDINGS: DCD lung transplants now account for about 20% of lung transplants in many centres and outcomes after transplantation have been excellent with this source of donation. Clinical experience using EVLP has shown the method to be well tolerated and allow for reassessment and improvement in function from high-risk donor lungs. When these lungs were transplanted, low rates of primary graft dysfunction were achieved and long-term survival was comparable with standard transplantation. Preclinical studies have shown a great potential of EVLP as a platform for the delivery of novel therapies to repair injured donor lungs. SUMMARY: A significant increase on the number of available lungs for transplantation is expected in the coming years with the wider use of DCD lungs and with organ-specific ex-vivo treatment strategies.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it