The Study of the Sense of Smell in Children: Development Prospects
Bibliographic record
Abstract
Background. Despite the fact that the study of the olfactory system is still difficult, the detection of dysosmia is promising for the diagnosis of a number of diseases. As a screening method, tests for the identification of various odors can be used. However, similar tests are developed and used for adults. In pediatrics, the use of such methods causes difficulty due to the cognitive and linguistic functions of the child, which are in the stage of development. Aim — to study olfactory function in children using an identification test. Methods. A diagnostic prospective study of 30 healthy children with no complaints of decreased olfactory function, living in the middle zone of the Russian Federation, mainly in the Moscow Metropolitan area, aged 11 to 14 y.o. was held. All children underwent a study of olfactory function using the University of Pennsylvania Smell Identification Test (UPSIT). To control all children, olfactometry was performed using a patented method for assessing the thresholds of olfaction in children, based on the use of various concentrations of aqueous solutions of valerian tincture, ammonia and acetic acid. Results. In the study of sense of smell with the help of an UPSIT test, hyposmia was detected in 30% of children, which was not confirmed later with the help of a threshold test. At the same time, when presenting some odorants, most of the answers were incorrect. Conclusions. The use of olfactory tests developed for adults in children does not reflect the real state of the olfactory system. It is required to create kits for the study of the olfactory function specifically for the children’s category of patients.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".