Abstract 39: Donating Automated External Defibrillators May Not Be Enough
Bibliographic record
Abstract
Background: In response to the out-of-hospital sudden death of their son, parents and friends established a local foundation in Tucson, Arizona to help prevent sudden cardiac death. One of their projects was to provide Automated External Defibrillators (AEDs) predominately to public and private schools, places of worship, boys and girls clubs and museums in Tucson, Arizona and surrounding area. Prior to receiving the AED, the majority of sites attended training in the use of the AED, that included information concerning the need to replace the electrodes pads before they expired. Methods: The first author of this abstract (a trained Emergency Medical Technician and a recent college graduate) visited sites that responded to the offer of assistance to retrain individuals in the proper use of their AED. Included in the visit, she determined the status of the donated AED and provided education about future maintenance. Results: Each site visited had received their AED between 7/2009 and 4/2011. Of the 36 sites visited, the majority of the units had potential problems. One had been stolen, and one was missing (2/36 or 6%). Of the remaining 34 units, 23/34 (68%) had outdated electrode pads, and in 2/34 (6%) the battery had expired. Thus only 11/34 (32%) were emergency ready. Of these, 7/11 had been donated within two years (the average shelf-life of AED electrode pads). The other 4/11 had replaced their expired AED electrode pads. Conclusions: Providing AEDs alone may not be the optimal approach. A system must be in place to assure that they are properly stored and maintained. AED pads with longer “shelf-life” should also be a goal of AED manufacturers.
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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 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".