Determination of Dimensions of Glenoid Cavity from other Scapular Parameters
Bibliographic record
Abstract
Background: Different pathological conditions are associated with the anatomical variations in glenoid cavity. For getting insights into these variations the anthropometric parameters knowledge is highly required. Objective: The purpose of the study was the determination of the anthropometric relationship present between the left and right side of the glenoid cavity of the scapula and the application of the obtained knowledge in the forensic medicine. Place and Duration: In the department of anatomy, Multan Medical and Dental College and Bacha Khan Medical Complex Swabi for six months duration, from January 2021 to June 2021. Material and Methods: The data of 190 patients included in the study, was collected from the anatomy department of our institute. The sample was withdrawn from the non-deformed and well macerated scapulae bone of the 190 patients. The calibrated sliding digital caliper was used to measure the anthropometric parameters of glenoid cavity. The glenoid height, width and index were calculated by SPSS software. Results: The 34.8±4.0 (R=38 ± 4.98 and L=27.9-46.78) and 24.9 ±3.90 (R=27.2 ± 3.43 and L=20.1- 36) was the calculated mean standard deviation of Maximum glenoid height (MGH) and Maximum glenoid width (MGW) respectively. The statistically significant and greater values of MGH and MGW on the right side were obtained by using ANOVA and t-test. While calculated values of glenoid Index (GI) was smaller on the right side as compared to the left. Conclusion: The kinanthropological applications of the scapula are indicated by the study that which side can be more commonly used. This study provides with in-depth knowledge of biological profiling and develops better understanding required during reconstruction of the damaged skeleton. Keywords: Glenoid cavity, Maximum glenoid height (MGH), Maximum glenoid width (MGW).
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".