Study on hearing loss and its relationship with work in pesticide-exposed tobacco growers
Bibliographic record
Abstract
ABSTRACT The Purpose of this case report is to present four cases of tobacco growers with hearing loss due to occupational exposure to pesticides. A qualitative case study comprising three cases of sensorineural hearing loss with causal nexus (Cases 1, 2 and 4), and one (Case 3) of sensorineural hearing loss compatible with ototoxicity by pesticides, with causal nexus mainly based on minor neuropsychiatric disorders. The sample was composed of rural workers with health problems, in working age, having started working early in life, exposed to various pesticides, including organophosphates. The auditory and neurovegetative symptoms reported were noise discomfort (n = 2), speech perception difficulty (n = 3), dizziness (n = 2), and imbalance (n = 2). The pure-tone audiometry revealed a sensorineural hearing loss in one or more high frequencies, and one of the cases presented alteration in the brainstem auditory evoked potentials. There is evidence, in this study, of an association between hearing loss and work in tobacco growers exposed to pesticides, with peripheral auditory damage in four cases, and central damage in one of them. Thus, the need for a complete audiological evaluation of pesticide-exposed populations is highlighted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".