Development of a MEMS-based sensor array to characterise<i>in situ</i>loads during scoliosis correction surgery
Bibliographic record
Abstract
Finite element analysis was implemented in three stages to design a piezoresistive, micro-electro-mechanical systems sensor array consisting of four-terminal sensors placed on deformable silicon diaphragms. This sensor array was used to retrofit the Contrel-Dubousset instrumentation in order to capture forces and moments applied by surgeons in real time during scoliosis correction surgery. Outputs from the sensor array have been designed to be compatible with a low-power wireless data transmission system that is currently being developed with a collaborating team in the biomedical industry. The designed sensor array is capable of resolving forces of up to 1000 N and moments of up to 4000 N mm in three dimensions during surgery. A process flow to produce the first prototyped version of this micro sensor with known performance characteristics is presented and tested. Acceptable correlation was found between the performance of the manufactured prototypes, numerical simulation and similar documented devices.
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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 | 0.000 |
| 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) | 0.001 | 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".