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Can the contralateral limb be used as a control during the growing period in a rodent model?

2018· article· en· W2810170823 on OpenAlexafffund
Tanvir Mustafy, Irene Londoño, Isabelle Villemure

Bibliographic record

VenueMedical Engineering & Physics · 2018
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsUniversité de MontréalPolytechnique MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPeriod (music)RodentPhysical medicine and rehabilitationControl (management)Rodent modelMedicineComputer scienceBiologyArtificial intelligenceInternal medicineEcologyPhysics

Abstract

fetched live from OpenAlex

The contralateral limb is often used as a control in various clinical, forensic and anthropological studies. However, no studies have been performed to determine if the contra-lateral limb is a suitable control during the bone development period. The aim of this study was to determine the bilateral symmetry of growing rat tibiae in terms of geometric shape, mechanical strength and bone morphological parameters with developmental stages. Left and right tibias of 18 male Sprague-Dawley rats at 4, 8 and 12 weeks of age were scanned with micro-CT for bone-morphometric evaluation and for 3D deviation analysis to quantify the geometric shape variations between left and right tibiae. Overall tibial lengths and curvatures were also measured, and bone mechanical strength was investigated using three-point bending tests. Deviation distributions between bilateral tibiae remained below 0.5 mm for more than 80% of the geometry for all groups. Tibial lengths, longitudinal tibial curvatures, bone-morphometric parameters and mechanical strengths changed significantly during the growing period but kept a strong degree of symmetry between bilateral tibiae. These results suggest that bilateral tibiae can be considered symmetrical in nature and that contralateral limb can be used as a control during the growing period in different experimental scenarios.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score0.412

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.012
GPT teacher head0.280
Teacher spread0.267 · 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 designSimulation or modeling
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

Citations9
Published2018
Admission routes2
Has abstractyes

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