Neck mass: Tularemia misdiagnosed as a possible malignancy
Bibliographic record
Abstract
Background: Tularemia is a zoonotic disease of the Northern Hemisphere caused by Francisella tularensis. Given its diverse animal reservoir and wide range of transmission modes, a thorough history of potential exposure is paramount. In the right context, fever combined with skin eruption and lymphadenopathy should raise the possibility of tularemia. Additionally, health care providers should be mindful that F. tularensis is a risk group 3 pathogen and a category A bioterrorism agent and presents a risk for laboratory personnel due to its aerosolization potential, low infectious dose, and fatality rate ranging from 2% to 60%. Method: Retrospective single chart review. Results: We describe a 65-year-old man with tularemia working as a bear-hunting guide whose management was delayed despite a fairly typical presentation due to lack of awareness regarding this disease. This case also demonstrates the need for safer referral practices and improved communications with the laboratory to ensure personnel are taking the appropriate measures while handling patient samples to avoid potentially serious consequences. Conclusion: The diagnosis was confirmed from a neck mass biopsy and the patient made a complete recovery with appropriate antibiotic treatment.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".