CERAMIC ANEURYSM CLIPS
Bibliographic record
Abstract
OBJECTIVE: To design and manufacture an aneurysm clip that incorporates ceramic jaws and a titanium spring, thereby decreasing susceptibility artifact at the aneurysm neck and allowing intra- and/or postoperative magnetic resonance (MR) evaluation. METHODS: A series of aneurysm clips were developed using ceramic jaws and a titanium spring. A corresponding clip applicator with a novel clip-applicator interface was developed to improve ergonomics and visibility during clip placement or removal. Ceramic clips were imaged at 3.0 T in a kiwi fruit phantom model and compared with MR-compatible Yaşargil aneurysm clips (Aesculap, AG & Co., Tuttlingen, Germany). Ceramic clips were subsequently evaluated in a human cadaveric model at 1.5 T. RESULTS: Ceramic clips were developed initially using silicon nitride ceramic and subsequently with yttria-stabilized zirconia ceramic. The ceramic clip jaws showed reduced susceptibility artifact compared with MR-compatible Yaşargil clips. Closing pressure was maintained over the course of 50 cycles of clip opening and closing. Aneurysm clip jaw crossing was not observed. The novel clip applicator and enhanced applicator-clip interface improved visibility during clip application and reduced the potential for torque during clip removal. CONCLUSION: The use of ceramic material limited MR imaging susceptibility artifact and image distortion in the area immediately surrounding the ceramic jaws. As expected, image distortion occurred around the titanium spring and pivot. However, in the unique design of this new aneurysm clip, the spring is located far enough from the distal end of the jaws to provide an undistorted image of the clipped area.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".