Wolf creek XVII part 4: Amplifying lay-rescuer response
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: Amplifying lay-rescuer response is a key priority to increase survival from out-of-hospital cardiac arrest (OHCA). We describe the current state of lay-rescuer response, how we envision the future, and the gaps, barriers, and research priorities that will amplify response to OHCA. Methods: 'Amplifying Lay-Rescuer Response' was one of six focus topics for the Wolf Creek XVII Conference held on June 14-17, 2023, in Ann Arbor, Michigan, USA. Conference invitees included international thought leaders and scientists in the field of cardiac arrest resuscitation from academia and industry. Participants submitted via online survey knowledge gaps, barriers to translation and research priorities for each focus topic. Expert panels used the survey results and their own perspectives and insights to create and present a preliminary unranked list for each category that was debated, revised and ranked by all attendees to identify the top 5 for each category. Results: The top five knowledge gaps as ranked by the panel, reflected a recognition of the need to better understand the psycho-social aspects of lay response. The top five barriers to translation reflected issues at the individual, community, societal, structural, and governmental levels. The top five research priorities were focused on understanding the social/psychological and emotional barriers to action, finding the most effective/cost-effective strategies to educate lay persons and implement community life-saving interventions, evaluation of new technological solutions and how to enhance the role of dispatch working with lay-rescuers. Conclusion: Future research in lay rescuer response should incorporate technology innovations, understand the "humanity" of the situation, leverage implementation science and systems thinking to save lives. This will require the field of resuscitation to engage with scholars outside our traditional ranks and to be open to new ways of thinking about old problems.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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 it