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Method for accurate removal of trabecular bone samples from a curved articulating surface of the distal femur

2024· article· en· W4394693349 on OpenAlexaff
James W. Scott, K. C. Geoffrey Ng, Alexander D. Liddle, Jonathan R.T. Jeffers

Bibliographic record

VenueClinical Biomechanics · 2024
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsRobarts Clinical TrialsWestern University
FundersNIHR Imperial Biomedical Research CentreEngineering and Physical Sciences Research CouncilImperial College LondonNational Institute for Health and Care Research
KeywordsPerpendicularFemurTrabecular boneCondyleMaterials scienceCore (optical fiber)Principal axis theoremBiomedical engineeringAnisotropyFEMORAL CONDYLEAnatomyOsteoporosisGeometryGeologyCartilageOpticsComposite materialMedicinePhysicsMathematics

Abstract

fetched live from OpenAlex

BACKGROUND: Knowing the mechanical properties of trabecular bone is critical for many branches of orthopaedic research. Trabecular bone is anisotropic and the principal trabecular direction is usually aligned with the load it transmits. It is therefore critical that the mechanical properties are measured as close as possible to this direction, which is often perpendicular to a curved articulating surface. METHODS: This study presents a method to extract trabecular bone cores perpendicular to a curved articulating surface of the distal femur. Cutting guides were generated from computed tomography scans of 12 human distal femora and a series of cutting tools were used to release cylindrical bone cores from the femora. The bone cores were then measured to identify the angle between the bone core axis and the principal trabecular axis. FINDINGS: The method yielded an 83% success rate in core extraction over 10 core locations per distal femur specimen. In the condyles, 97% of extracted cores were aligned with the principal trabecular direction. INTERPRETATION: This method is a reliable way of extracting trabecular bone specimens perpendicular to a curved articular surface and could be useful across the field of orthopaedic research.

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)0.003
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.148
GPT teacher head0.470
Teacher spread0.322 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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