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Record W2980265762

Design and development of a handcycle car rack

2019· article· en· W2980265762 on OpenAlexaboutno aff
Arshdeep Singh Saran, Harjit Singh Grewal, Jaswinder Singh Johal, Santanjot Singh Dhaliwal

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsnot available
Fundersnot available
KeywordsRackWheelchairVariety (cybernetics)Reliability (semiconductor)EngineeringComputer scienceAeronauticsTransport engineeringWorld Wide WebMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

Handcycling is a popular hobby carried out by many individuals. A few of these individuals are however in a wheelchair and transporting their personal hand-cycle can lead to astray of difficulties. Most of these difficulties involve the user in the wheelchair having no assistance to mount the hand-cycle to the car in an efficient, safe and effective way. This is where the introduction of a handcycle car rack takes place. There are a variety of handcycle car racks on the market today however the reliability, durability and ease of use is always in question when it comes to the car racks currently used. The price of some of these is astronomical and just not affordable for the majority of wheelchair users. Also, with the use of electrical components raises the issue of reliability of the rack especially in the harsh climates that occur in the Vancouver area. Throughout this project, the team and the client have been closely working together to come up with a handcycle car rack that can be easily used by the client while using no electrical components.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.013
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.007

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 head0.128
GPT teacher head0.435
Teacher spread0.307 · 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
Published2019
Admission routes1
Has abstractyes

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