Replicating interbody device subsidence with lumbar vertebrae surrogates
Bibliographic record
Abstract
Bone surrogates are proposed alternatives to human cadaveric vertebrae for assessing interbody device subsidence. A synthetic vertebra with representations of cortices, endplates and cancellous bone was recently developed as an alternative surrogate to polyurethane foam blocks. The ability of the two surrogates to replicate subsidence has not been fully assessed, and was evaluated by indenting them with ring-shaped indenters and comparing their performance with human cadaveric vertebrae using qualitative characteristics and indentation metrics. The sensitivity of each surrogate to a centrally or peripherally placed indenter was of particular interest. Many indentation characteristics of the foam blocks were similar to those of human cadaveric vertebrae, except their insensitivity to centrally and peripherally placed indenters, owing to their homogeneous mechanical properties. This is distinctly different from the cadaveric vertebrae, where a peripherally placed indenter indented significantly less than a centrally placed indenter, because of endplates. By contrast, the synthetic vertebra was sensitive to peripherally placed indenters owing to its bi-material composition, including a thickened peripheral endplate. However, an overly strong synthetic endplate resulted in unrepresentative indentation shape and depth. Both surrogates produced similar results to human cadaveric vertebrae in certain respects, but neither is accurate enough in terms of material property distribution to model subsidence completely in human cadaveric vertebrae.
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.
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 | 0.002 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".