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Record W4389673820 · doi:10.1080/21681163.2023.2282074

Development of a single-vertebra image-based technique to quantify shoulder kinematics using four-dimensional computed tomography

2023· article· en· W4389673820 on OpenAlex

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 and Biomedical Engineering Imaging & Visualization · 2023
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsRobarts Clinical TrialsLawson Health Research InstituteSt Joseph's Health CareWestern University
Fundersnot available
KeywordsTorsoKinematicsVertebraBiomechanicsCoordinate systemTomographyComputer scienceMathematicsArtificial intelligenceComputer visionAnatomyMedicineRadiologyPhysics

Abstract

fetched live from OpenAlex

This paper introduces and validates a new technique for analysing six degrees-of-freedom shoulder kinematics using four-dimensional computed tomography (4DCT), which uses a single vertebra to reference thoracic motion.Differences between the vertebra and International Society of Biomechanics (ISB) torso coordinate systems had an average RMSE of 11.6 and no statistical differences were found regarding range of motion.The errors associated with repeated analysis ranged from 0.2 mm to 3.4 mm, and 0.9 to 1.1.Overall, the technique has been shown to be repeatable, and using a single vertebra is comparable to using the ISB torso coordinate system.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.767
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
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 head0.067
GPT teacher head0.393
Teacher spread0.327 · 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