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Record W4414533843 · doi:10.1186/s42466-025-00403-1

The use of robotic arms for individuals with severe upper-limb disabilities

2025· letter· en· W4414533843 on OpenAlexafffund
Noémie Fortin-Bédard, Orthelo Léonel Gbètoho Atigossou, Véronique H. Flamand, Jason Bouffard, François Routhier

Bibliographic record

VenueNeurological Research and Practice · 2025
Typeletter
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsCentres Intégré Universitaires de Santé et de Services SociauxCentre intégré universitaire de santé et de services sociaux de la Capitale-NationaleUniversité LavalCentre for Interdisciplinary Research in Rehabilitation
FundersFonds de Recherche du Québec - Santé
KeywordsObservational studyAmyotrophic lateral sclerosisMEDLINERobotic armRehabilitationRobotics

Abstract

fetched live from OpenAlex

This letter to the editor aims to comment on the article « User expectations and experiences of an assistive robotic arm in amyotrophic lateral sclerosis: a multicenter observational study » recently published by Spittel et al. (Neurol Res Pract, 6(1), 42).

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)0.003
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.030
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0300.017
Insufficient payload (model declined to judge)0.0030.004

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 head0.457
GPT teacher head0.543
Teacher spread0.085 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2025
Admission routes2
Has abstractyes

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