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Record W2138728510 · doi:10.1109/iembs.2008.4650543

Measurement of current density vectors in a live pig for the study of human electro-muscular incapacitation devices

2008· article· en· W2138728510 on OpenAlexaff
T.P. DeMonte, Jia‐Hong Gao, Dinghui Wang, Weijing Ma, M.L.G. Joy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsUniversity of TorontoFields Institute for Research in Mathematical Sciences
Fundersnot available
KeywordsCurrent (fluid)Current densityMeasure (data warehouse)Biomedical engineeringComputer sciencePhysicsElectrical engineeringMedicineEngineeringData mining

Abstract

fetched live from OpenAlex

Current density imaging (CDI) is an MRI technique used to quantitatively measure current density vectors in biological tissue. A CDI sequence and corresponding experimental method were developed for the study of human electro-muscular incapacitation (HEMI) devices using an animal model. Measurements of current density vectors were performed in piglets weighing 4 to 5 kg. Pathways of current density vectors in the region of the chest and heart were investigated using vector plotting and streamline integration methods. Measurement of current density vectors were also used to analyze the relationship between applied current amplitude and measured current density magnitude in the range of 10 mA to 45 mA of applied current.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.079
GPT teacher head0.319
Teacher spread0.240 · 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

Citations5
Published2008
Admission routes1
Has abstractyes

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