Understanding the pain experience of lionfish envenomation
Bibliographic record
Abstract
Introduction: Stings from the lionfish (Pterois volitans) constitute one of the most painful wounds in the ocean. This species has invaded the Atlantic coast of the United States, Gulf of Mexico, Caribbean, and Mediterranean Sea. In addition to its ecological impact on local fish populations, stings from the lionfish pose a medical problem because of the debilitating nature of the pain they produce. However, there are no studies examining the human pain experience of lionfish stings. Objective: To characterize the various aspects of the pain experience following a lionfish sting. Methods: We developed a pain questionnaire that includes validated scales used with patients having acute or chronic pain to understand the pain variability, as well as the use of health care resources and treatments. Results: We provide the first study of the pain experience from lionfish stings. Here, we show that the pain is intense from the start and peaks approximately 1 hour later, resolving itself in 7 days for most victims. Furthermore, pain intensity can be influenced by several factors, including (1) age of the victim, where older victims experience significantly higher pain intensities, (2) the number of spines involved, (3) and whether infection occurred at the injury site. However, pain intensity was not different between male and female participants. Conclusion: These findings will inform the medical community on the pain experience and can be used by local authorities to better appreciate the impact of lionfish envenomations to develop programs aimed at curtailing the expansion of the lionfish.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".