Anatomical Variations in Fissure of the Lung on Computed Tomography
Bibliographic record
Abstract
Objective: Lung fissures embryologically separate the bronchopulmonary segments from each other. We aimed to detect anatomical variations in fissures in patients who underwent thoracic computed tomography (CT). Materials and Methods: All the patients underwent a thoracic CT examination between July 1 - July 15, 2022. The patients’ gender, lung fissures continuity, accessory fissures presence, and variation side were recorded. The frequency of fissures was compared between the genders using the chi-square test. Results: The study included a total of 352 patients (211 men, 141 women). A total of 105 variations were detected in 95/352 (26.99%) of the patients, 61/211 (28.91%) were male, 34/141 (24.11%) were female. The right oblique fissure was incomplete in nine (2.6%), and the right horizontal fissure was incomplete in 14 (4%) patients and absent in 14 (4%). The left oblique fissure was observed to be incomplete in 16 (4.5%) patients. A total of 52 (14.8%) accessory fissures were detected. Conclusion: In the literature, a wide variety of fissure variations have been reported. Due to this diversity, having good knowledge of the fissure anatomical architecture is essential when performing surgical procedures and interpreting radiological images to clinically identify the location of bronchopulmonary segments.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".