Irregular porous titanium enhances implant stability and bone ingrowth in an intra‐articular ovine model
Bibliographic record
Abstract
Abstract Two commercially available porous coatings, Gription and Porocoat, were compared for the first time in a challenging intra‐articular, weight‐bearing, ovine model. Gription has evolved from Porocoat and has higher porosity, coefficient of friction, and microtextured topography, which are expected to enhance bone ingrowth. Cylindrical implants were press‐fit into the weight‐bearing regions of ovine femoral condyles and bone ingrowth and fixation strength evaluated 4, 8, and 16 weeks postoperatively. Biomechanical push‐out tests were performed on lateral femoral condyles (LFCs) to evaluate the strength of the bone‐implant interface. Bone ingrowth was assessed in medial femoral condyles (MFCs) as well as implants retrieved from LFCs following biomechanical testing using backscattered electron microscopy and histology. By 16 weeks, Gription‐coated implants exhibited higher force (2455 ± 1362 vs. 1002 ± 1466 N; p = 0.046) and stress (12.60 ± 6.99 vs. 5.14 ± 7.53 MPa; p = 0.046) at failure, and trended towards higher stiffness (11,510 ± 7645 vs. 5010 ± 8374 N/mm; p = 0.061) and modulus of elasticity (591 ± 392 vs. 256 ± 431 MPa; p = 0.061). A strong, positive correlation was detected between bone ingrowth in LFC implants and failure force ( r = 0.93, p < 10 −13 ). By 16 weeks, bone ingrowth in Gription‐coated implants in MFCs was 10.50 ± 6.31% compared to 5.88 ± 2.77% in Porocoat ( p = 0.095). Observations of the bone‐implant interface, made following push‐out testing, showed more bony material consistently adhered to Gription compared to Porocoat at all three time points. Gription provided superior fixation strength and bone ingrowth by 16 weeks.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".