The Splenic Artery and Segmental Branches Morphometric Study in Humanoid Cadaver Spleens by Method of Dissection
Bibliographic record
Abstract
Human spleen has various functions including immune system regulation and haematopoisis. The spleen is an extremely vascularized and fragile organ. It is the second major lymphatic organ, containing 25% of lymphoid tissue in the body, and has haematologic and immunologic roles. Objective: To understand the segmental branches morphometry of the polar and splenic arteries. Methods: The analysis was performed on 86 spleens collected from adult human cadavers of not known gender, stored in 10% formalin solution. In the Department of Anatomy, Mohi-ud-Din Islamic Medical College (MIMC), Mirpur, Azad Jammu & Kashmir and Women Medical and Dental College Hospitals, Abbottabad for six- months duration from July-December 2021 Results: In 59 (68.6%) spleen samples; there were 2 primary branches, 23 (26.7%) samples had three primary branches, and 4 (4.7%) specimens had four primary branches. 20 (23.3%) samples had superior polar arteries, 34 (39.5%) had inferior polar arteries, and both inferior and superior polar arteries in 7 (8.1%) samples. The inferior polar artery length ranged from 0.9-5.90 cm, with 3.17 cm of average length and 3.30 cm median length. The superior PB diameter ranged from 0.8-4.12 mm, with 2.20 mm average length and 2.4 mm median length. The mean diameter of middle PB ranged from 0.8 mm to 3.6 mm, with an average of 2.10 mm and 2.4 mm median length. The superior polar artery diameter ranged from 0.5-3.1 mm, with 1.40 mm average length and 1.4 mm of median. The inferior polar artery diameter varies from 0.5-2.9 mm, with 1.3 mm of an average diameter with 1.4 mm median. Conclusions: As various splenic sparing surgeries depend on a better information of the vascular anatomy of the spleen, this analysis enhances the current information about the segmental branches’ morphometry of the splenic artery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".