Bibliographic record
Abstract
Heating loss associated with aging,also known as presbycusis,seriously affects the comnmnicative abili- ties and compromises the lite styles of the elderly people in China.Presbycusis and its consequences have caught the attention of the country today.Efforts have been made to help the elderly;however,lack of well ducumented demographic data on the prevalence of presbycusis has significantly hampered the efforts to establish infrastructures for effective aural rehabilitation and clinical managemeut of the elderly people suffering from auditory deficits and other communicative difficulties. This paper intends to review the existed research articles,published in Chinese,on presbycusis and intervention,and to present our view of the present status of research in this direction.It should be noted that,there is considerable variahility in the outcomes of the studies because of inadequate study designs and poor controls of all measurement parameters.Only a few studies were carried OUt tO determine the prevalence of central auditory processing disorder(CAPD)and other cognitive dys- functions associated with elderly population in the country.The use of hearing aids is low among hearing impaired seniors.In the end,the authors will discuss the reasons that the present research on presbycusis is lagging behind and possible solutions that will he explained and shared.(Chin J Ophthalmol and Otorhinolaryngol,2007,1:9-13)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".