A technique for intraoperative creation of patient-specific titanium mesh implants
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Prefabricated, patient-specific alloplastic implants for cranioplasty reduce surgical complexity, decrease operative times, minimize exposure and risk of contamination, and have resulted in improved aesthetic results. However, in creating a prefabricated custom implant using a patient's computed tomography data, a stable, unalterable defect must be clearly defined before surgery. In the event that an intraoperative modification of an exiting skull defect is required, or in cases of tumour resection in which the size of the skull defect is unknown preoperatively, these prefabricated implants cannot be used. The ideal method for alloplastic cranioplasty would enable cost-effective creation of a patient-specific implant with the capacity for intraoperative modification. The present article describes a novel technique of cranioplasty that uses a patient's computed tomography data to create a custom forming tool (ie, mold), enabling intraoperative creation of a patient-specific titanium mesh implant. The utility of these implants in creating a custom reconstructive solution in cases in which the size of the skull defect is unknown preoperatively will be demonstrated using two case presentations.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it