A New Simple Radiological Scoring System for Classifying the Tegmen of the Mastoid
Bibliographic record
Abstract
Results: Twenty one papers were identified which were relevant to our search.In total, 686 implants were inserted and 121 (17.6%) showed evidence of trauma.The cochleas with trauma had basilar membrane elevation in 10.5%, ruptured in 12.9%, the electrode passed from the ST to the scala vestibuli (SV) in 71.8% and there was grade 4 trauma consisting of spiral lamina or modiolus fracture and tear of the SV, in 4.8%.The studies used a variety of histological and radiological methods to assess for evidence of trauma.A majority (57%) used histology either alone or with radiology (CT or x-ray).A majority of studies used cadaveric temporal bones (67%).Conclusions: Minimising cochlear trauma during implant insertion is important to preserve residual hearing and optimise audiological performance.An overall 17.6% trauma rate suggests that CI could be improved with more accurate and consistent electrode insertion such as robotic guidance.The correlation of cochlear trauma with post-operative hearing has yet to be determined.
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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.027 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".