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Record W2750956904 · doi:10.1177/1558944717726372

Dynamic CT Scan of the Normal Scapholunate Joint in a Clenched Fist and Radial and Ulnar Deviation

2017· article· en· W2750956904 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

VenueHand · 2017
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Surgery and Rehabilitation
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsWristMedicineUlnar deviationFistScapholunate ligamentRange of motionRadiographyNuclear medicineOrthodonticsAnatomyRadiology

Abstract

fetched live from OpenAlex

BACKGROUND: Injuries to the scapholunate can have severe long-term effects on the wrist. Early detection of these injuries can help identify pathology. The purpose of this study was to evaluate the motions of the scapholunate joint in normal wrists in a clenched fist and through radial and ulnar deviation using novel dynamic computed tomography (CT) imaging. METHODS: Fifteen participants below 40 years of age consented to have their wrist scanned. Eight participants were randomized to have the right wrist scanned and 7 the left wrist. Volunteers were positioned at the back of the gantry with the wrist placed on the table, palmar side down. Participants began with the hand in a relaxed fist position and then proceeded through an established range of motion protocol. Dynamic CT imaging was captured throughout the range of motion. RESULTS: The movement in the healthy scapholunate joint through a clenched fist and radial and ulnar deviation is minimal. The averages were 1.19, 1.01, and 0.95 mm, representing the middle, dorsal, and volar measurements, respectively. CONCLUSIONS: This novel dynamic CT scan of the wrist is a user-friendly way of measuring of the scapholunate distance, which is minimal in the normal wrist below 40 years of age.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.125

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.011
GPT teacher head0.252
Teacher spread0.241 · 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