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Record W2899519037 · doi:10.3791/58084

Using a Knee Arthrometer to Evaluate Tissue-specific Contributions to Knee Flexion Contracture in the Rat

2018· article· en· W2899519037 on OpenAlexaff
T. Mark Campbell, Katherine Reilly, Louis Goudreau, Odette Laneuville, Hans K. Uhthoff, Guy Trudel

Bibliographic record

VenueJournal of Visualized Experiments · 2018
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsOttawa HospitalÉlisabeth Bruyère HospitalUniversity of Ottawa
Fundersnot available
KeywordsKnee JointContractureRange of motionMedicineJoint ContractureMuscle contracturePhysical medicine and rehabilitationKnee flexionComputer scienceAnatomyPhysical therapySurgery

Abstract

fetched live from OpenAlex

Normal knee range of motion (ROM) is critical to well-being and allows one to perform basic activities such as walking, climbing stairs and sitting. Lost ROM is called a joint contracture and results in increased morbidity. Due to the difficulty of reversing established knee contractures, early detection is important, and hence, knowing risk factors for their development is essential. The rat represents a good model with which the effect of an intervention can be studied due to the similarity of rat knee anatomy to that of humans, the rat's ability to tolerate long durations of knee immobilization in flexion, and because mechanical data can be correlated with histologic and biochemical analysis of knee tissue. Using an automated arthrometer, we demonstrate a validated, precise, reproducible, user-independent method of measuring the extension ROM of the rat knee joint at specific torques. This arthrometer can be used to determine the effects of interventions on knee joint ROM in the rat.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.150
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.059
GPT teacher head0.502
Teacher spread0.443 · 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.

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

Citations4
Published2018
Admission routes1
Has abstractyes

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