Bibliographic record
Abstract
PURPOSE: To assess the problems associated with the Bioceramic (Aluminum oxide, Al(2)O(3)) orbital implant. METHODS: A consecutive case series of 107 patients receiving a Bioceramic orbital implant by two surgeons over a 3-year period were reviewed. The authors analyzed patient age, type of surgery, size of implant, peg system, follow-up duration, time of pegging, complications encountered, and treatment. RESULTS: Seven patients were lost to follow-up after 2 months, leaving 100 patients who were followed from 3 to 38 months (average, 13.4 months). Three patients died during the follow-up period (one with 2 months' follow-up, one with 7 months' follow-up, and the third with 9 months' follow-up). Implant-related problems occurred in 11 (11%) patients. Discharge occurred in 5 (5%) patients, implant exposure in 2 (2%), socket discomfort in 1 (1%), trochleitis in 1 (1%), and conjunctival thinning in 2 (2%). Peg problems occurred in 11 (34.3%) of 32 pegged patients: discharge in 4 (12.5%) and in 1 patient (3.1%) each, pyogenic granuloma, conjunctiva overgrowing the peg, implant exposure around the sleeve, clicking, accumulation of black material, and broken peg during insertion. Infection did not occur in any patient. CONCLUSIONS: The Bioceramic orbital implant represents an alternative porous orbital implant that is biocompatible with orbital tissues, easy to manufacture, structurally strong, and less expensive than other commercially available porous orbital implants (e.g., Bio-Eye hydroxyapatite implant). Problems encountered with its use are similar to those seen with the Bio-Eye orbital implants but appear to occur less often. The incidence of exposure associated with the Bioceramic implant is less than that reported for the Bio-Eye.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".