Are you ready for an office code blue? : online video to prepare for office emergencies.
Bibliographic record
Abstract
PROBLEM BEING ADDRESSED: Medical emergencies occur commonly in offices of family physicians, yet many offices are poorly prepared for emergencies. An Internet-based educational video discussing office emergencies might improve the responses of physicians and their staff to emergencies, yet such a tool has not been previously described. OBJECTIVE OF PROGRAM: To use evidence-based practices to develop an educational video detailing preparation for emergencies in medical offices, disseminate the video online, and evaluate the attitudes of physicians and their staff toward the video. PROGRAM DESCRIPTION: A 6-minute video was created using a review of recent literature and Canadian regulatory body policies. The video describes recommended emergency equipment, emergency response improvement, and office staff training. Physicians and their staff were invited to view the video online at www.OfficeEmergencies.ca. Viewers' opinions of the video format and content were assessed by survey (n = 275). CONCLUSION: Survey findings indicated the video was well presented and relevant, and the Web-based format was considered convenient and satisfactory. Participants would take other courses using this technology, and agreed this program would enhance patient care.
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 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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".