Mass Casualty Incidents and Disaster Participation in Real versus Simulated Events in Romania
Bibliographic record
Abstract
Abstract Background: The current study outlines some of the main particularities of both real and simulated mass casualty incidents (MCI) and disasters in Romania as reported by medical and paramedical participating personnel. Methods: A non-profit organization in Romania trained 1250 doctors, nurses and paramedics for proper MCI interventions through a dedicated programme for the last part of the year 2013. Half a year later, an email with a unique link to an online questionnaire was sent to each participant to assess their opinion over the participation in real or already simulated MCI or disasters. The questionnaire consisted of 25 specific topics, out of which only a fraction were considered for the current study. Results: Out of all participants, 145 doctors, 184 nurses and 115 paramedics provided valid answers, totaling 444 responders. Most participants were satisfied with the information about the location and type of the incident they would respond to. The amplitude of a given event is generally well anticipated under simulation conditions as compared to real events, where the amplitude tends to be higher rather than lower than expected (p=0.0082). About three quarters of participants under real or simulated events repeated or demanded repeating the information trafficked through mobile radios, almost a quarter misinterpreted the information, and almost a half reported delayed operations due to miscommunication. Conclusions: Simulations are a proper method of communication evaluation for mass casualty incidents and disasters, which can also stress the common communication issues encountered during a real MCI unfolding.
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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 | 0.001 |
| 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".