Hydroscopic Properties of Organic Objects That May Present as Aural Foreign Bodies
Bibliographic record
Abstract
BACKGROUND: Organic foreign bodies swell when irrigated with water, potentially making extraction more difficult. As the degree and rate of swelling of different types of organic foreign bodies has not been established, we aimed to analyze the hydroscopic properties of different organic foreign bodies in body temperature water. METHODS: Dry kidney beans, brown beans, peas, popcorn kernels, and dried fruits were soaked in a body temperature (37C) water bath. Volume of these organic materials was measured hourly to 8 hours, then at 12, 16, 24, 28, 36 and 48 hours. RESULTS: All dried fruits and beans increased in volume over time. The volume increase from baseline at 6 hours was between 43% (popcorn kernels) and 383% (kidney beans). Peas, popcorn, and raisins did not increase volume further after 6 hours. Kidney and brown beans had the greatest increase in volume overall (1268% and 482% respectively), and the greatest continued increase after 24 hours. CONCLUSIONS: Many organic substances that frequently present as aural foreign bodies may swell enough in water to lodge tightly in the ear canal. Typical popcorn kernels and dried peas will not swell sufficiently to lodge tightly in the ear canal of a typical child one year or older. A retained organic foreign body in a moist ear canal may cause inflammation until the foreign body can be removed. These risks may be offset by the advantages of successful removal with irrigation. KEYWORDS: Foreign body; Irrigation; Organic; Ear; Hydroscopic; Procedure; Removal.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".