National Burn Repository 2006: A Ten-Year Review
Bibliographic record
Abstract
This article presents findings from the National Burn Repository (NBR) 2006 Annual Report. Data reported herein cover a 10-year period from January 1, 1996, through June 30, 2006. This year's report includes the first comparative presentations of data over time to show what appear to be trends in the dataset. The purpose of this report is to share information about the current state of care for burned patients in the United States. Some of the implications include epidemiology, burn-prevention efforts, research, education, acute care and quality improvement in burn programs, resource allocation, and reimbursement issues. The 2006 NBR Report covers a 10-year rolling period of acute initial burn admissions. As in previous years, records were excluded from analysis if the patient status was readmission, admission for reconstruction or rehabilitation, elective admission, outpatient encounter, duplicate encounter, or other acute nonburn admission. Records also were excluded from analysis if they contained missing values for gender or if hospital length of stay was less than intensive care unit days.
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 | 0.024 | 0.073 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.024 | 0.023 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.009 |
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".