Do prosthetic limbs really have to cost an arm and a leg?
Bibliographic record
Abstract
With the average cost of commercially available prosthetics ranging from $4,000 to $75,000 CAD, these essential devices are inaccessible to physically disabled people. Production expenses of the various prosthesis types required for each individual’s functional needs will continue increasing in coming years. This is one of the many factors that contributes to health inequities affecting those with physical disabilities in the Canadian healthcare system. Prosthesis coverage across the country is highly variable; many individuals are forced to rely on personal resources, fundraising, or contributions from non-governmental organizations (NGOs) to meet this basic healthcare need. The Institute for Research on Public Policy and Statistics Canada reports that disabled individuals are more likely to be unemployed, have lower median incomes, and be less likely to graduate with a university degree than those without a disability, further contributing to this disparity. As a team, we address the cost barrier of prostheses by establishing Brachïum: a humanitarian initiative focused on creating an affordable, 3D printed, open-source transradial prosthesis prototype that could eventually be distributed to marginalized communities to improve their quality of life.
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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".