Bibliographic record
Abstract
Volume X, No. 1 February 2009 NEWSLETTER Open Access at www.westjem.org California Chapter of the American Academy of Emergency Medicine The Right Change for the Right Reasons President’s Message INSIDE: President’s Message (continued) S Swadron Bailout Nation D Brosnan The Imperative to Support SC Gabaeff W CAL/AAEM Membership Application Publication Order Form hen I emigrated to the United States from Canada in the 1990s, it seemed as though substantive change in the U.S. healthcare system would never come. Hillary Clinton’s bold proposals had been roundly defeated and there appeared to be little appetite for a plan to provide universal coverage for all Americans. The Los Angeles County/USC Medical Center where I work was crumbling from within, and foreign medical students that came to observe remarked that our facility reminded them more of their developing-world electives in Africa than of their home base hospitals in Europe. What a difference a decade has made. Now, we appear to be on the precipice of real change. A new government is taking shape in Washington with a mandate for healthcare reform, and the American Medical Association is running an advertisement campaign entitled “Voice for the Uninsured.” At the Los Angeles County/ USC Medical Center, we have moved into a beautiful new one billion dollar replacement facility, which is now the same gleaming testament to our highest ideals that the old Art Deco building must have been during the Great Depression, towering over downtown Los Angeles. It is somewhat ironic that during our many years of national surplus and excess, we did so little to address the problem of uninsured and underinsured patients – one might expect that such initiatives would come when times are good. But with the recent economic downturn, people are losing their jobs, their homes and their medical insurance. We are seeing more and more patients in the emergency department at the county hospital that one wouldn’t normally expect to see – people with complex organ transplants and in the middle of extensive cancer treatments that have suddenly found themselves with nowhere else to turn. We also know that little has changed with regard to the vital signs of our patient population. You have all heard it by now from a variety of sources. We lag behind most developed nations on multiple healthcare indices including preventable mortality, basic preventative care and access to timely care. We are also the only developed nation where hundreds of thousands of people must claim personal bankruptcy due to outstanding healthcare bills. And all of this is going on despite the fact that as a nation we spend a wildly disproportionate and ever-increasing amount on healthcare – approximately double what other developed nations spend. As belts tighten and budgets shrink, we as emergency physicians will naturally feel continued on page 2
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.149 | 0.073 |
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".