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Record W4417126327 · doi:10.1097/sap.0000000000004593

Reliability and Validity of Individual Finger Flexor Strength Measurement Using the Martin Vigorimeter

2025· article· en· W4417126327 on OpenAlexaff
Hyung Jin Chung, Seung Hoo Lee, Sang‐Bum Kim

Bibliographic record

VenueAnnals of Plastic Surgery · 2025
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsReliability (semiconductor)BulbFlexor musclesMeasurement deviceLittle finger

Abstract

fetched live from OpenAlex

OBJECTIVE: While numerous tools exist for grip strength measurement, there is a lack of research for assessing the individual finger flexor strength. This study aimed to evaluate the test-retest reliability of measuring individual finger flexion strength in healthy adults using the smallest bulb of the Martin Vigorimeter (MV). METHODS: Grip strength of 100 adults without hand pathology was measured using the large bulb of the MV, while individual finger flexor strength was assessed using the small bulb. Measurements were repeated after 3 weeks to evaluate test-retest reliability. Contribution of each finger flexor was calculated and compared to the previously reported values obtained using specialized equipment or protocol. RESULTS: The MV showed excellent reliability for grip strength (intraclass correlation coefficient > 0.9) and good-to-excellent reliability for individual finger flexor strength (intraclass correlation coefficient = 0.805-0.914). The middle finger contributed the most (approximately 30%), followed by the index and ring fingers (25%-26%), which were comparable to values previously reported using specialized equipment or protocols. Normalized minimal detectable change values for finger flexor strength ranged from 9.7% to 14.2%. CONCLUSIONS: These findings suggest that the smallest bulb of the MV is a reliable and accessible tool for measuring individual finger flexor strength in healthy adults, with results comparable to those obtained using specialized equipment or protocols.

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)0.002
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.604
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.223
GPT teacher head0.323
Teacher spread0.100 · 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
Published2025
Admission routes1
Has abstractyes

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