The impact of hearing loss on cognitive function and its assessment
Bibliographic record
Abstract
The population of the developed countries is aging, thus the number of older people is increasing. At the same time the proportion of the diseases connected with the age is rising. When a person ages, his cognitive function fades away as well. Researchers have long noted that cognitive function of the elderly with defective hearing fades away faster than in normally hearing people. There are several theories explaining it, but this issue is still a matter of debate. Several researches were held recently regarding the impact of cochlear implantation on the level of cognitive function in the preoperative and postoperative periods. Controversial results were received which require further study of the issue. HI-MoCA and RBANS-H special test systems have been developed lately for the hearing impaired. These tests allow you to evaluate the change in cognitive function in people with hearing impairment, up to complete deafness. The tests are original MoCA and RBANS, but are adapted for people with hearing impairment. Thanks to these new instruments we will be studying the change of cognitive function in preoperative and postoperative periods which will allow us to evaluate the role of hearing in the decline in cognitive function of the elderly.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".