Agger‐bullar classification (ABC) of the frontal sinus drainage pathway: validation in a preclinical setting
Bibliographic record
Abstract
BACKGROUND: The anatomy of structures surrounding the frontal sinus drainage pathway (FSDP) is extremely complex and challenging for endoscopic sinus surgeons. The anatomical nomenclature of this area reflects this complexity and lack of agreement regarding anatomical variants of this region is present in the literature. This work presents a new classification system of the air spaces surrounding the FSDP, called the agger-bullar classification (ABC), and compares it with the most widely used anatomical classification of the frontoethmoidal region, the modified Bent and Kuhn classification (MBKC). METHODS: Fourteen human heads underwent cone beam computed tomography (CT) scan and subsequently endoscopic dissection. Anatomical data were collected by 2 radiologists in consensus, an expert surgeon, and a novice surgeon. The radiologists filled the anatomical report after examining the CT scan, and the expert surgeon had both CT scan and endoscopic dissection available. A record of the dissection was obtained to allow the novice surgeon to compile the report. Interrater agreement regarding each variable of the classification systems was estimated through Cohen's kappa value. Cohen's kappa values of variables referring to the same anatomical subunit were matched to compare ABC with MBKC. RESULTS: For both air spaces in front and behind the FSDP, interrater agreement values of the variables of the ABC were significantly higher than the corresponding variables of the MBKC. CONCLUSION: This preclinical study demonstrates the potential of the ABC system. Although the ABC may improve preoperative anatomical assessment of the frontoethmoidal area, validation in a clinical setting is required.
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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 | 0.015 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".