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Record W1556523519 · doi:10.5405/jmbe.828

[no title]

2011· article· en· W1556523519 on OpenAlexafffund
Michael P. Willand

Bibliographic record

VenueJournal of Medical and Biological Engineering · 2011
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health ResearchU.S. Public Health Service
KeywordsStimulationBiomedical engineeringMedicinePhysical medicine and rehabilitationInternal medicine

Abstract

fetched live from OpenAlex

Traditionally, animal studies employing electrical stimulation for conditioning denervated muscle rely on 24-hour-based stimulation paradigms, most employing implantable stimulators. While these stimulators provide the necessary current to cause muscular contraction, they have problems with battery life, programmability, and long-term robustness. Continuous 24-hour stimulation, while shown to be effective in animals, is not easily translatable to a clinical setting. It is also difficult to evaluate animal comfort and muscular contraction throughout a 24-hour period. We have developed a system and stimulation paradigm that can stimulate up to five animals at one time for one hour per day. The constant current stimulator is a USB-powered device that can, under computer control, output trains of pulses with selectable shapes, widths, durations and repetition rates. It is an external device with no implantable parts in the animal except for the stimulating electrodes. We tested the system on two groups of rats with denervated gastrocnemius muscles. One group was stimulated using a one-hour-per-day, 5-days-per-week stimulation paradigm for one month, while the other group had electrodes implanted but received no stimulation. Muscle weight and twitch force were significantly larger in the stimulated group than the non-stimulated group. Presently, we are using the stimulator to investigate electrical stimulation coupled with other therapeutic interventions that can minimize functional deficits after peripheral nerve injuries.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.005

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 head0.118
GPT teacher head0.254
Teacher spread0.137 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations20
Published2011
Admission routes2
Has abstractyes

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