Data concerning AED registration in the Danish AED Network, and cardiac arrest-related characteristics of OHCAs, including AED coverage and AED accessibility
Bibliographic record
Abstract
The data presented in this article is supplemental data related to the research article entitled "Automated external defibrillator accessibility is crucial for bystander defibrillation and survival: a registry-based study" (Karlsson et al., 2019). We present detailed data concerning: 1) the type of location for deployed and registered automated external defibrillators (AEDs) in the nationwide Danish AED Network; 2) the number of registered AEDs in the nationwide Danish AED Network, and changes in AED registration (according to year and type of AED location); 3) the number of AEDs being withdrawn from the AED network between the years 2007-2016. We also report data on baseline cardiac arrest-related characteristics of out-of-hospital cardiac arrests (OHCAs) that occurred in Copenhagen, Denmark, between 2008 and 2016. Cardiac arrest-related characteristics are further described according to AED accessibility (accessible vs. inaccessible AED at the time of OHCA) for OHCAs covered by an AED (AED ≤200 m route distance of an OHCA). Finally, we report data on distance to the nearest accessible AED for bystander defibrillated OHCAs covered by an AED ≤200 m route distance where the AED was inaccessible at the time of OHCA.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".