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Record W2137193924 · doi:10.1109/86.830959

A mechanical arthrometer to measure knee joint contracture in rats

2000· article· en· W2137193924 on OpenAlexafffund
Guy Trudel, Paul O’Neill, Louis Goudreau

Bibliographic record

VenueIEEE Transactions on Rehabilitation Engineering · 2000
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsCentre for Interdisciplinary Research in RehabilitationUniversity of Ottawa
FundersDalhousie UniversityUniversité Laval
KeywordsJoint ContractureContractureSoft tissueKnee JointMuscle contractureReproducibilityMedicineJoint (building)OrthodonticsBiomedical engineeringBiomechanicsPhysical medicine and rehabilitationRange of motionDisplacement (psychology)StiffnessAnatomySurgeryMathematicsStructural engineeringEngineeringPsychology

Abstract

fetched live from OpenAlex

Animal models for joint diseases are necessary for in vivo studies. Joint contractures are characterized by lack of the normal range of motion of a joint most often due to increased soft tissue stiffness. Biological and biochemical data have been obtained but biomechanical data on small animals are rare. An instrument was developed to measure rat knee angular displacement at various soft tissue loads in normal and pathological circumstances. This article describes the instrument and reports its reproducibility and accuracy. The reproducibility and accuracy of this instrument was found to be acceptable thereby validating its use for research purposes with adult rat knees.

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)0.003
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.008
GPT teacher head0.232
Teacher spread0.224 · 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

Citations12
Published2000
Admission routes2
Has abstractyes

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