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Record W4379659637 · doi:10.24908/agt.v1i1.16122

Automated Cold, Compression, and Heat Gloves for Arthritis: A Proposal for Combination Therapy

2023· article· en· W4379659637 on OpenAlexaff
Maya Morcos, Amir‐Ali Golrokhian‐Sani

Bibliographic record

VenueAging and (Geron) Technology · 2023
Typearticle
Languageen
FieldMedicine
TopicIntramuscular injections and effects
Canadian institutionsQueen's University
Fundersnot available
KeywordsPain reliefMedicineCompression therapyProgrammerCompression (physics)Physical therapyComputer scienceSurgery

Abstract

fetched live from OpenAlex

Compression, heat, and cold therapy are commonly recommended for arthritis at-home pain relief. A combination of all three therapies would be beneficial to provide ease of use and autonomy for patients. A new proposed pain-relief solution involves gloves that combine compression, heat, and cold. These gloves would provide patients with an efficient and convenient pain relief method inside or outside the house. Specifically, they would provide compression and heat settings that can automatically turn off after a set time. With the help of a clinician programmer, daily cold therapy time can be scheduled for long-term treatment. This technology may initially be limited by its cost and accessibility, but those issues should recede with further developments.

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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.004
Open science0.0020.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0110.006

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 head0.011
GPT teacher head0.292
Teacher spread0.281 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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 routes1
Has abstractyes

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