(IN) ACCESS TO ARTIFICIAL LIMBS: THE PATIENT’S PERSPECTIVE ACCORDING TO THE WAR AMPS OF CANADA
Bibliographic record
Abstract
Funding agencies, both public and private, do not adequately meet the needs of Canadian amputees. This often leaves amputees without access to appropriate prosthetic care due to outstanding balances that are to be paid out of pocket, or by charitable organizations. There are several factors that result in these inadequacies. As healthcare is a provincial responsibility in Canada, provinces and territories have the authority to create individual public regimes, each with their own weaknesses. In fact, there are a few provincial regimes which do not include prosthetic funding at all. Private healthcare is meant to offset the remaining balance; however, their lack of knowledge regarding amputation has resulted in the creation of policies with ambiguous language, limiting the funding available for prosthetic care. Attitudinal barriers and missed legislative opportunities further exacerbate the shortcomings of prosthetic funding provided by public and private funding agencies, requiring action. Article PDF Link:https://jps.library.utoronto.ca/index.php/cpoj/article/view/35972/28331 How To Cite: Petlock A, DiMario K. (In) Access to artificial limbs: the patient’s perspective according to the WAR AMPS of Canada. Canadian Prosthetics & Orthotics Journal. 2021; Volume 4, Issue 2, No.13. https://doi.org/10.33137/cpoj.v4i2.35972 Corresponding Author: Annelise PetlockThe War Amps Advocacy Program/ 2827 Riverside Drive Ottawa, Ontario, Canada.E-Mail: annelise.petlock@waramps.caORCID ID: https://orcid.org/0000-0002-7273-4527
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".