What’s in a Name? Recent Key Projects of the Committee on Organization and Delivery of Burn Care
Bibliographic record
Abstract
The Committee for the Organization and Delivery of Burn Care (ODBC) was charged by President Palmieri and the American Burn Association (ABA) Board of Directors with presenting a plenary session at the 45th Meeting of the ABA in Palm Springs, CA, in 2013. The objective of the plenary session was to inform the membership about the wide range of the activities performed by the ODBC committee. The hope was that this session would encourage active involvement within the ABA as a means to improve the delivery of future burn care. Selected current activities were summarized by key leaders of each project and highlighted in the plenary session. The history of the committee, current projects in disaster management, regionalization, best practice guidelines, federal partnerships, product development, new technologies, electronic medical records, and manpower issues in the burn workforce were summarized. The ODBC committee is a keystone committee of the ABA. It is tasked by the ABA leadership with addressing and leading progress in many areas that constitute current challenges in the delivery of burn care.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".