Association between residence location and likelihood of transplantation among pediatric dialysis patients
Classification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".
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
Many children with ESRD reside far from a kidney transplant center. It is unknown whether this geographical barrier affects likelihood of transplantation. We used data from a national ESRD database. Patients ≤ 18 yr old who started renal replacement in nine Canadian provinces during 1992-2007 were followed until death or last contact. Primary outcome was kidney transplantation (living or deceased donor). Distance between nearest pediatric transplant center and each patient's residence was categorized as: <50, 50 to <150, 150 to <300, and ≥ 300 km. Using survival analysis, we compared likelihood of transplantation between whites and non-whites living in various distance categories. Among 728 patients, 52.2% were males and 62.5% were whites. Compared to white children living < 50 km from a transplant center, white (HR, 0.73; 95% CI, 0.56-0.95) and non-white (HR, 0.66; 95% CI, 0.48-0.92) children living ≥ 300 km away were less likely to receive a transplant. Non-white children living < 50 km away (HR, 0.59; 95% CI 0, 45-0.78) were also less likely to receive a transplant compared to otherwise similar whites living < 50 km away. Although equitable access to transplantation by residence location is observed among remote-dwelling adults with ESRD, white and non-white children with ESRD living ≥ 300 km from a transplant center were less likely to receive transplants.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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