Record W4249921849 · doi:10.1109/tnsre.2022.3143052

IEEE Transactions on Neural Systems and Rehabilitation Engineering publication information

2021· article· en· W4249921849 on OpenAlexfundno aff

Shankar Subramaniam, Laura Wolf, Carolyn McGregor, Daniel P. Ferris, Editor-In-Chief Crayton, Pruitt Family, Kara Mcarthur, Susan Kathy, Land, K Liu, Kathleen Kramer, Ellen Randall, Toshio Fukuda, Stephen Phillips, Educational Activities, Lawrence Hall, Maike Luiken, J. C. Matthews, Roger Fujii, Katherine Duncan, Dalma Novak, Stephen Welby, Chris Brantley, Karen Hawkins, Steven Heffner, Donna Hourican, C.M. Jankowski, Geographic Activities, Konstantinos Karachalios, Ieee-Standards Association, Jamie Moesch, Sophia Muirhead, Thomas Siegert, Mary Ward-Callan

Bibliographic record

VenueIEEE Transactions on Neural Systems and Rehabilitation Engineering · 2021

Typearticle

Languageen

FieldEngineering

TopicMuscle activation and electromyography studies

Canadian institutionsnot available

FundersIndian Institute of Technology IndoreNational Chiao Tung UniversityShanghai Jiao Tong UniversityZhejiang UniversitySapienza Università di RomaUniversidad Pública de NavarraKungliga Tekniska HögskolanNIH Clinical CenterNational Rehabilitation CenterAalborg UniversitetUniversity of TwenteVictoria UniversityMonash UniversityUniversity of SheffieldIndian Institute of Technology GandhinagarTechnische Universiteit DelftIndian Institute of Technology PalakkadMeiji UniversityBritish Columbia Institute of TechnologyAuckland University of Technology, New ZealandFlorida Institute of TechnologyUniversity of GlasgowUniversidad Técnica Federico Santa MaríaUniversity of California, DavisShanghai Educational Development FoundationWorcester Polytechnic InstituteUniversity of Texas Health Science Center at HoustonUniversity of WaterlooUniversity of South CarolinaFudan UniversitySwinburne University of TechnologyUniversity of PittsburghNational Institutes of HealthSan Diego State UniversityUniversity of Central FloridaKorea Institute of Science and TechnologyHuazhong University of Science and TechnologyNorth Carolina State UniversityUniversity of WashingtonRijksuniversiteit GroningenUniversity of PatrasUniversity of Southern California

KeywordsRehabilitationRehabilitation engineeringComputer scienceNeural systemPhysical medicine and rehabilitationMedicinePsychologyNeurosciencePhysical therapy

DOI10.1109/tnsre.2022.3143052

Abstract

fetched live from OpenAlex

No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.002

Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated

Candidate categoriesInsufficient payload (model declined to judge)

Consensus categoriesnone

DomainCandidate signal: none · Consensus signal: none

Study designCandidate signal: Not applicable · Consensus signal: Not applicable

GenreCandidate signal: Other · Consensus signal: Other

Teacher disagreement score0.735

Threshold uncertainty score0.888

Distilled classifier scores by category (both heads)

Category	Codex	Gemma
Metaresearch	0.001	0.002
Meta-epidemiology (narrow)	0.001	0.000
Meta-epidemiology (broad)	0.001	0.000
Bibliometrics	0.002	0.001
Science and technology studies	0.000	0.000
Scholarly communication	0.002	0.002
Open science	0.001	0.001
Research integrity	0.001	0.001
Insufficient payload (model declined to judge)	0.265	0.133

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 head0.006

GPT teacher head0.193

Teacher spread0.187 · 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