MétaCan
Menu
Back to cohort
Record W2017197060 · doi:10.1109/acssc.2014.7094448

A review of source separation and source localization approaches in peripheral nerves

2014· review· en· W2017197060 on OpenAlex
José Zariffa

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venue2014 48th Asilomar Conference on Signals, Systems and Computers · 2014
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsUniversity Health NetworkToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsSource separationComputer scienceInterface (matter)CuffNeurophysiologyPeripheralNeurosciencePeripheral nervous systemPeripheral nerveBiomedical engineeringMedicineArtificial intelligenceAnatomyCentral nervous systemBiologySurgery

Abstract

fetched live from OpenAlex

Selectively monitoring the messages encoded in the electrical activity of peripheral nerves would enable us to improve the control of neuroprosthetic devices, which interface with the nervous system to help restore function after neurological injuries or amputations. By using multi-contact nerve cuff electrodes, which measure the electric potentials at several locations on the surface of the nerve, this task can be approached as an inverse problem of source localization. This review focuses on the attempts that have been made to apply source separation and source localization approaches to multi-contact nerve cuff recordings, and discusses future directions for these efforts.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.828
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.119
GPT teacher head0.316
Teacher spread0.197 · 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