Bibliographic record
Abstract
I would like to thank the Members of the Western Trauma Association for the opportunity to serve as your President for the past year. There are many reasons why I enjoy being part of this organization. The cultivation of lasting friendships, the camaraderie and collegiality of the scientific meetings and the family atmosphere that has been created make the Western Trauma Association one of the best kept secrets in American surgery. The memories that I have of our annual meetings often make me reflect on the priorities that we set for our careers. Skiing with my children throughout the West and Canada, having my sons be on a first name basis with leaders in the field of trauma and watching them take off with the “pack” not caring whether I was present or not was sometimes painful, but always gratifying. The title of my presidential address came from a communication I had with one of my former hospital administrators. He approached me about a critically ill trauma patient that I was caring for in the intensive care unit, saying, “Dr. Petersen, what are we going to do about the ethical conundrum concerning Case JC?” He did not say, “Mr. JC” or “your patient JC,” just “Case JC.”
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 | 0.044 | 0.148 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.032 |
| Scholarly communication | 0.014 | 0.021 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.020 | 0.029 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".