Design and Manufacture of a Custom Ligament Loading Device for Use with Second Harmonic Generation Microscopy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ligament insertions into bone (entheses) represent a natural adaptation to severe material mismatch. Load is transferred from relatively flexible connective tissue to relatively inflexible bone over typically not more than a millimeter. Adequate load transfer at an insertion site is necessary for normal joint function while preventing injury. A few models have been used to assess different aspects of insertional mechanics, but all suffer from limitations. Most importantly, there has been an inability to observe the behaviour of entheses under applied load. An accurate description of enthesis load transfer mechanics has thus been lacking. A relatively new and powerful microscopic technology, second-harmonic generation (SHG), for which the University of Calgary has recently acquired an advanced microscope, has been shown to image movement on a microscale and is a promising tool to overcome the first of these difficulties, microscopic observation. The remaining difficulty remains the precise loading of ligaments during SHG imaging, highlighting the need for a custom-built loading device. Ligament loading is not an unfamiliar procedure and commercially available equipment exists to do so, however, the infrastructure for simultaneously loading and microscopically imaging entheses does not exist.The purpose of this work is to detail the device design process, from concept to manufacture, emphasizing the solutions to the design’s unique constraints and objectives and how they were determined. This includes the consolidation of a number of custom-machined components and commercially available hardware (for example: linear rail guides, strain gauges and precision motors).
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.
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 | 0.000 | 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) | 0.000 | 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 it