Management of Benign Middle Ear Tumors: A Series of 7 Cases
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Benign middle ear tumors represent a rare group of neoplasms that vary widely in their pathology, anatomy, and clinical findings. These factors have made it difficult to establish guidelines for the resection of such tumors. Here we present 7 unique cases of these rare and diverse tumors and draw from our experience to recommend optimal surgical management. Based on our experience, a postauricular incision is necessary in nearly all cases. Mastoidectomy is required for tumors that extend into the mastoid cavity. Whenever exposure or hemostasis is believed to be inadequate with simple mastoidectomy, canal-wall-down mastoidectomy should be performed. Finally, disarticulation of the ossicular chain greatly facilitates tumor excision and should be performed early in the procedure.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it