Bibliographic record
Abstract
As a Canadian observer and participant, I offer the following opinions about the recently concluded Boston meeting concerning the morbidity and mortality of dialysis in the United States of America. First, I congratulate Americans for having the courage to execute a meeting that catalyzed a disturbing discussion about imperfect technologies and poor patient outcomes in their country. Thank you Drs. Steinman, Parker, and Hull and members of the steering committee. Canada has never had such a meeting. Although our mortality rates are lower than the United States (1), key intermediate outcomes show signs of getting worse over time (2). In a setting with universal health insurance, our central venous catheter (CVC) rate has reached an appalling 45% in prevalent patients, and we have no fistula-first initiative (3,4). This is our national tragedy. There is much for America to be commended about. The conference concluded with the assertion that the science is clear and that the next steps are fairly obvious. As stated by the giants of the field and supported by the rank and file, it appears there is a pragmatic consensus about the major …
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 | 0.016 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.021 | 0.042 |
| Insufficient payload (model declined to judge) | 0.024 | 0.011 |
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".