Surgical anatomy of the parapharyngeal space: Multiperspective, quantification‐based study
Bibliographic record
Abstract
BACKGROUND: Several surgical approaches to the parapharyngeal space (PPS) have been proposed. An objective description of advantages and limitations of the surgical routes is lacking. METHODS: Ten cadaver heads were dissected using the transnasal (medial, lateral), sublabial, transoral (transpharyngeal, transvestibular, transmandibular), transcervical (transcervical, transparotid, transmandibular, transmastoid), and type C and D infratemporal approaches. Neurovascular and musculoskeletal structures encountered were analyzed. A navigation-based quantification of working volume and exposure of PPS compartments was accomplished. RESULTS: Transnasal approaches exposed the upper PPS, though with limited working volume. Transoral approaches exposed the middle PPS, minimizing neurovascular structures crossed. Only transcervical and skull base approaches exposed the entire PPS, crossing several neurovascular structures. CONCLUSION: A tentative systematization of the surgical approach(es) to PPS in relation to different targets is provided: unicompartmental resection can be performed with a single, conservative access, whereas multicompartmental dissections frequently require a wider or multiportal approach.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".