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Record W2322957815 · doi:10.7863/ultra.15.06105

Normal Sonographic Anatomy of the Wrist With Emphasis on Assessment of Tendons, Nerves, and Ligaments

2016· review· en· W2322957815 on OpenAlexaff
Salvatore Gitto, Ferdinando Draghi

Bibliographic record

VenueJournal of Ultrasound in Medicine · 2016
Typereview
Languageen
FieldMedicine
TopicOrthopedic Surgery and Rehabilitation
Canadian institutionsUniversity Hospital Foundation
Fundersnot available
KeywordsWristMedicineAnatomySoft tissueRadiology

Abstract

fetched live from OpenAlex

Sonography allows for rapid, cost-effective, noninvasive, and dynamic evaluation of soft tissue structures, thus representing a valuable tool for ruling out musculoskeletal disorders of the wrist. Because of the complexity of the wrist joint, sonographic training and familiarity with normal and variant anatomy are needed to avoid misdiagnosis and improper treatment. The aim of this article is to enlighten readers about the structures representing normal findings or common variants during sonographic evaluations of the wrist. The main text reviews the pertinent gross anatomy and procedures that are recommended to assess the soft tissue structures of the wrist, with particular emphasis given to tendons, nerves, and ligaments. Detailed explanations of the scanning techniques and sonographic appearance of the wrist structures are provided in the figure legends.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.022
GPT teacher head0.372
Teacher spread0.350 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations55
Published2016
Admission routes1
Has abstractyes

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