MétaCan
Menu
← Back to cohort

Nascent Access Technologies for Individuals with Severe Motor Impairments

2011· book-chapter· en· W4246103022 on OpenAlexaff
Sarah Power, Saba Moghimi, Brian Nhan, Tom Chau

Bibliographic record

VenueIGI Global eBooks · 2011
Typebook-chapter
Languageen
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsExploitFace (sociological concept)Access technologyInstrumentation (computer programming)Emerging technologiesComputer scienceNeurosciencePsychologyHuman–computer interactionData scienceTelecommunicationsComputer securityArtificial intelligenceSociology

Abstract

fetched live from OpenAlex

As the number of individuals without physical access to communication or environmental interaction escalates, there are increasing efforts to uncover novel and unconventional access pathways. In this chapter, we introduce three emerging access technologies for individuals with severe disabilities: near-infrared spectroscopy, electroencephalographic measurement of visually-evoked potentials and infrared thermographic imaging of the face. The first two technologies harness activity directly from the brain while the third exploits spontaneous temperature changes in the face. For each technology, we discuss the physiological underpinnings, the requisite instrumentation, the scientific evidence to date and the future outlook.

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)0.001
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 score0.023
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0230.009

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 head0.041
GPT teacher head0.284
Teacher spread0.243 · 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
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueIGI Global eBooks→Same topicEEG and Brain-Computer Interfaces→French-language works237,207→