High-Fidelity Microsurgical Simulation: The Thiel Cadaveric Nerve Model and Evaluation Instrument
Bibliographic record
Abstract
With surgical education moving from a time-based to a competency-based model, developing high-fidelity simulation models has become a priority. The Thiel cadaveric model has previously been used for a number of medical and surgical simulations, including microvascular simulation. We aim to investigate the use of the Thiel model in peripheral nerve simulation and validate a novel evaluation instrument. Sixteen residents ranging from postgraduate years 1 to 6 participated in the study. Their nerve coaptations using Thiel cadaveric nerves were video recorded and evaluated by 5 fellowship-trained microsurgeons using the Micro-Neurorrhaphy Evaluation Scale (MNES). The intraclass correlation among the 5 evaluators was 0.75, revealing excellent interrater reliability. The Cronbach α was .77, underlining the internal consistency of the test items. Bivariate analysis revealed a significant association between the MNES scores and the participants' self-declared level of experience. This correlation was confirmed by mixed modeling. Our results validate the MNES and underscore the utility of the Thiel nerve tissue for peripheral nerve surgical simulation.
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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 | 0.001 | 0.001 |
| 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 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".