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Record W4390341293 · doi:10.1080/10255842.2023.2298371

Biomechanical effects of different loads and constraints on finite element modeling of the humerus

2023· article· en· W4390341293 on OpenAlex
Sabrina Islam, Kunal Manoj Gide, Emil H. Schemitsch, Habiba Bougherara, Radovan Zdero, Z. Shaghayegh Bagheri

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComputer Methods in Biomechanics & Biomedical Engineering · 2023
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsToronto Rehabilitation InstituteUniversity Health NetworkToronto Metropolitan UniversityVictoria HospitalWestern University
Fundersnot available
KeywordsFinite element methodHumerusStructural engineeringBiomechanicsOrthodonticsComputer scienceEngineeringMedicineAnatomy

Abstract

fetched live from OpenAlex

Currently, there is no established finite element (FE) method to apply physiologically realistic loads and constraints to the humerus. This FE study showed that 2 'simple' methods involving direct head loads, no head constraints, and rigid elbow or mid-length constraints created excessive stresses and bending. However, 2 'intermediate' methods involving direct head loads, but flexible head and elbow constraints, produced lower stresses and bending. Also, 2 'complex' methods involving muscles to generate head loads, plus flexible head and elbow constraints, generated the lowest stresses and moderate bending. This has implications for FE modeling research on intact and implanted humeri.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.751
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.031
GPT teacher head0.340
Teacher spread0.309 · 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