Morphometry relevant to Anterior Petrosectomy with special reference to Kawase’s Triangle
Bibliographic record
Abstract
Abstract Background and aims :The petrous apex and the middle cranial fossa is a commonly explored area in neurosurgeries and hence require a holistic approach which should include the possibility of anatomical variants and morphometric dissimilarities. Material and Methods:This morphometric study was undertaken on 91 dry adult skulls [182 petrosal apices] to analyze a number of parameters relevant to Anterior Petrosectomy [AP] via the Kawase’s Triangle [KT]. The anatomical landmarks most pertinent to Anterior Petrosectomy [Kawase's approach] were defined, recorded and validated. The findings of the study were compared with earlier workers who have employed other means of investigation viz. dry bones/CT scans or cadaveric studies . Results : The parameters undertaken for the study presented with variable values and moresoever for the surface area of the KT. This can be very logically attributed to the variant anatomy amongst races and also to the physiological status of the individual Conclusions : AP has evolved as a preferred method for approaching petroclival region and thus requires an in depth understanding. The present analysis throws significant light on certain parameters that would be helpful in making anterior petrosectomy safer. Surgeries of the skull base demand for high end precision and proficiency and thus our findings provide enhanced alertness for a better and safe procedure. A methodical approach to the area with the background knowledge of these parameters shall culminate in desired neurosurgical outcomes.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".