Bibliographic record
Abstract
With this third issue of Advances in Pulmonary Hypertension in 2007, I must first recognize the enormous success of the Pulmonary Hypertension Resource Network Symposium held in Crystal City, Virginia this October. Attendance was a record 400+ (up from 60 in 2003), and the representation was far-reaching, with attendees and participants from Oregon to Washington, DC, and Canada to Texas. This clearly reflects the tremendous interest in this growing field and speaks to the success of PHA in its mission to promote pulmonary hypertension awareness.Associate Editor Erika Berman Rosenzweig, MD, has taken the role of Lead Editor of this issue and with Editorial Board member Kristin Highland, MD, has put together a comprehensive review of pulmonary arterial hypertension (PAH) related to congenital heart disease (CHD), with three key pieces focused on CHD. Dr Ingram Schulze-Neick provides an overview of pulmonary vascular disease in CHD, while Dr Michael Landzberg covers emerging medical therapies, and Drs Konstantinos Dimopoulos and Michael Gatzoulis teach us about how to evaluate operability in adults with CHD, as well as the role of pretreatment with targeted PAH therapy. A specialist roundtable discussion is a highlight of this issue, as it covers the practical aspects of treating patients with CHD and associated PAH. Dr Berman Rosenzweig and her contributors are to be congratulated for their efforts in producing such a wonderful issue of Advances.
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 | 0.017 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.016 | 0.016 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.015 | 0.032 |
| Insufficient payload (model declined to judge) | 0.042 | 0.030 |
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".