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Record W2589543108 · doi:10.1017/s0022215116005533

The mastoid tegmen: A new clinical radiological classification

2016· article· en· W2589543108 on OpenAlexaff
Allan Ho, Sherif Idris, Youness Elkhalidy, Ravi Bhargava

Bibliographic record

VenueThe Journal of Laryngology & Otology · 2016
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Anomalies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineRadiological weaponSurgery

Abstract

fetched live from OpenAlex

differences have been identified (lower in ethnic Chinese compared to Malays and Indians).Data estimating the prevalence of hearing loss in ageing Singaporeans is scant.Thresholds of >40 dB in the better ear were found in 54% and in at least one ear in 87%.Untreated hearing loss in the elderly results in significant decline in the quality of life of both the individual and their family.Self-perception of hearing loss is a very poor indicator of the presence of hearing loss.Between 20 and 33% of hearing impaired seniors were willing to consider a hearing aid; between 23 and 83% felt that it was unnecessary.Seniors who are independent in their activities of daily living (ADLs) are more likely to consider hearing aids than those who are ADL dependent and housebound.Conclusions: Hearing loss and cognitive impairment will become increasing public health concerns.Further studies assessing whether the treatment of hearing loss can slow the rate of cognitive decline among older adults are required.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.001
Science and technology studies0.0010.002
Scholarly communication0.0020.004
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.003

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.

Opus teacher head0.071
GPT teacher head0.362
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations2
Published2016
Admission routes1
Has abstractyes

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