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Record W3178286639 · doi:10.21203/rs.3.rs-690831/v1

Bioimpedance Measurement of Knee Injuries using Bipolar Electrode Configuration

2021· preprint· en· W3178286639 on OpenAlexaff
Xuanjie Ye, Lexi Wu, Kaining Mao, Yiwei Feng, Xianfeng Lin, Jie Chen

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldMedicine
TopicBody Composition Measurement Techniques
Canadian institutionsUniversity of Alberta
FundersChina Scholarship Council
KeywordsMedicineElectrodeKnee JointBiomedical engineeringPhysical medicine and rehabilitationPhysical therapySurgeryPhysics

Abstract

fetched live from OpenAlex

Abstract Currently, there is no suitable solution for the point-of-care of knee injuries. A potential portable and low-cost technique for accessing and monitoring knee injuries is bioimpedance measurement. This study validated the feasibility of the bipolar electrode configuration for knee bioimpedance measurements with two electrodes placed on a fixed pair of knee acupuncture locations called Xiyan. Then, the study collected 82 valid samples to investigate the relationship between bioimpedance and knee injuries, among whom 45 patients, each with one healthy knee and one injured knee, and 37 individuals all with healthy knees. The self-contrast results indicated that knee injuries caused a reduction of bioimpedance of the knee by about 5% on average, which was detectable at around 100 kHz (p ≈ 0.001). Furthermore, the results analyzed by principal component analysis and support vector machines show that the detection sensitivity can reach 91.11% using the leave-one-out cross-validation.

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 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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.059
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.156
GPT teacher head0.429
Teacher spread0.273 · 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 teacher head, not a consensus.

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
Published2021
Admission routes1
Has abstractyes

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