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Record W4390114902 · doi:10.33137/cpoj.v6i2.42222

3D PRINTING IN PROSTHETICS, ORTHOTICS AND ASSISTIVE TECHNOLOGY: MYTH AND REALITY

2023· editorial· en· W4390114902 on OpenAlexaffvenueabout
Silvia Raschke

Bibliographic record

VenueCanadian Prosthetics & Orthotics Journal · 2023
Typeeditorial
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsBritish Columbia Institute of Technology
Fundersnot available
KeywordsOrthoticsBespokeAssistive technologyMainstreamComputer scienceMedicinePhysical medicine and rehabilitationBusinessHuman–computer interactionPolitical scienceAdvertising

Abstract

fetched live from OpenAlex

3D printing initially captured the public eye when mainstream media began writing about Enabling the Future, a volunteer network that had begun designing and 3D printing prosthetic hands. Many of the stories focused on how this technology was going to disrupt the prosthetic sector. The response from prosthetists was skepticism and concern, in particular warning that 3D printed components would not be robust enough to withstand the activities of daily living. Moreover, they emphasized that fit problems could potentially cause more harm than good. Several years on, this issue explores currant usage and experiences with the technology in prosthetics and, to a limited extent, orthotics. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/42222/32280 How To Cite: Raschke S.U. 3D printing in prosthetics, orthotics and assistive technology: myth and reality. Canadian Prosthetics & Orthotics Journal. 2023; Volume 6, Issue 2, No.1. https://doi.org/10.33137/cpoj.v6i2.42222E-Mail: silvia-raschke-cpoj@online-publication.com ORCID ID:https://orcid.org/0000-0001-7964-4295

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.524
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.228
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEditorial

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".

Quick stats

Citations2
Published2023
Admission routes3
Has abstractyes

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