Collaborative iIslet Transplant Registry.
Bibliographic record
Abstract
The Collaborative Islet Transplant Registry (CITR) was established in 2001 with support from the National Institute of Diabetes and Digestive Diseases to collect and analyze information on islet transplants in North America. Thirteen of 27 invited islet transplant centers from the United States and Canada were already participants as of January 2004 with 5 additional centers awaiting IRB approval. In October 2003, CITR had preliminary data on 58 recipients of 107 islet transplants performed at the 13 member centers. These islet recipients averaged 41 years of age (SD 8.9), had diabetes for almost 28 years (SD 10.2) and were predominantly (67%) female. Islets were procured from 118 deceased donors whose average age was 42 (SD 12.2), weight was 90 kg (SD 23.5), and BMI was 30.5 (SD 7.9). The time from cross-clamp to pancreas recovery averaged 56 minutes (SD 134.6). An average of 7,127 islets (SD 2,973) were infused per kg of the recipient's weight. Outcome data are still pending as the Registry prepares its first annual report. Here we describe the organization, goals and design of the data collection instruments for CITR.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.057 | 0.019 |
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".