Behavior of Various Orbital Implants Under Axial Compression
Bibliographic record
Abstract
PURPOSE: To determine and compare the amount of force required to disrupt the integrity of various orbital implants. METHODS: Compression tests were carried out by using a servo-electrical universal testing system on orbital implants including aluminum oxide (Bioceramic implant, FCI, Issy-Les-Moulineaux, France), coralline hydroxyapatite (HA) (Bio-Eye, Integrated Orbital Implants, Inc., San Diego, CA, U.S.A.), bovine HA (Molteno M-Sphere, IOP Inc., Costa Mesa, CA, U.S.A.), synthetic HA (FCI3, FCI, Issy-Les-Moulineaux, France), Chinese HA (H + Y Comprehensive technologies, Philadelphia, PA, U.S.A.), polylactic acid (Kinsey Nash Corporation, Duluth, MN, U.S.A.), porous polyethylene (Medpor, Porex Surgical Inc., College Park, GA, U.S.A.), and polymethylmethacrylate. RESULTS: Two basic groups of implants were identified: those that eventually reach a critical compression point and collapse (coralline HA, aluminum oxide, synthetic FCI3 HA, bovine HA, Chinese HA, and polymethylmethacrylate), and those that do not collapse but gradually compress with increasing load (porous polyethylene, polylactic acid). For similar-sized implants, the critical collapse point was earliest for the FCI3 HA implant, followed by the coralline HA, aluminum oxide, and polymethylmethacrylate implants. Smaller-sized collapsible implants showed earlier critical collapse points than larger-sized implants of similar material. CONCLUSIONS: A technique was established to assess the force required to disrupt the integrity of various orbital implants that is reliable, unbiased, and repeatable with any orbital implant. Orbital implants of different materials and sizes demonstrate different degrees of integrity. It is important to use similar-sized implants when comparing the integrity of different implant materials because size influences the force required to overcome the structural integrity of the implant.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".