Use of Cortoss™ as an Alternative Material in Calvarial Defects
Bibliographic record
Abstract
A clinical series of 13 patients who underwent cranioplasty using a new quick setting material, namely Cortoss, was done over 3-year period. Thus, the primary objective of this study is to evaluate the role of Cortoss in the treatment calvarial defects which were mainly due to trauma (4 patients), tumor or tumor-like lesions (5 patients), middle cerebral infarction (3 patients), and gun shot wound (1 patient). The surgical technique was found to be simple and effective. Long-term follow-up (mean 24.3 months) demonstrated satisfactory results in terms of surgical (functional) and cosmetic outcomes. None of the patients developed complications including infections, foreign body reactions or material leakage. The results led us to suggest that the use of Cortoss in the case of calvarial defects seems to be safe, effective, quick, and a feasible method for cranioplasty. We conclude that the mechanical, immunologic, and technical-grafting properties of Cortoss, together with its superior esthetic and psychological effects, probably will make it the best material for cranioplasty.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".