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Record W2015466993 · doi:10.1115/sbc2012-80356

Collapsible Load Bearing Assistive Standing Device for Paraplegics

2012· article· en· W2015466993 on OpenAlexaff
Jennifer Book, Isabel Cristina Orozco Giraldo, Sean D. Peterson

Bibliographic record

VenueASME 2012 Summer Bioengineering Conference, Parts A and B · 2012
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMuscle tonePhysical medicine and rehabilitationParaplegiaComputer scienceMedicineSpinal cord

Abstract

fetched live from OpenAlex

There are several health benefits to persons with spinal cord injuries and other mobility related disabilities achieved by standing and load bearing for a period of time, such as enhancing psychological well-being, maintaining vital organ capacity, and reducing abnormal muscle tone and spasticity [1]. Assistive standing devices for paraplegics are normally used while individuals are attending rehabilitation centers, as these devices are often impractical or undesirable for home use. Designs of standing structures for paraplegics that are currently available on the market often take up too much floor space in the home and are expensive, costing up to $2500. Therefore, in order to extend the health benefits of standing to paraplegics with limited floor space, budget, and/or a dislike of bulky medical devices in their home, it would be beneficial to have an inexpensive, aesthetically appealing, small-footprint option available for personal use.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0230.005

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.

Opus teacher head0.162
GPT teacher head0.414
Teacher spread0.252 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2012
Admission routes1
Has abstractyes

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