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Record W2126616385 · doi:10.1121/1.4933705

Ultrasonic guided waves in bone system with degradation

2015· article· en· W2126616385 on OpenAlexaff
Dhawal R. Thakare, Pierre Bélanger, Prabhu Rajagopal

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2015
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsAnisotropyUltrasonic sensorCortical boneMaterials scienceAcousticsOsteoporosisFinite element methodGuided wave testingBiomedical engineeringPhysicsOpticsMedicineAnatomy

Abstract

fetched live from OpenAlex

This paper investigates the feasibility of using ultrasonic guided waves for assessing the cortical bone and hence detect conditions such as osteoporosis. Guided wave propagation in bone systems modeled as multi-layered tubular structures consisting of anisotropic bone filled with viscous marrow and surrounded by tissue is studied using the Semi Analytical Finite Element (SAFE) method. Effects of changes to cortical bone thickness and mechanical properties are investigated. An attempt is also made to consider bone anisotropy in the models.The results, validated by experiments with bone phantoms, show that material and geometric condition strongly impacts the velocity of guided waves supported in the bone system. Identification of optimal guided wave modes for practical assessment is also discussed.

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)0.000
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.035
GPT teacher head0.319
Teacher spread0.283 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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