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Record W2899239607 · doi:10.3899/jrheum.180834

Physical Examination — Still Relevant in Sjögren Syndrome

2018· letter· en· W2899239607 on OpenAlexvenueno aff
R. Hal Scofield

Bibliographic record

VenueThe Journal of Rheumatology · 2018
Typeletter
Languageen
FieldMedicine
TopicSalivary Gland Disorders and Functions
Canadian institutionsnot available
FundersNational Institutes of HealthU.S. Department of Veterans Affairs
KeywordsMedicinePhysical examinationRheumatoid arthritisStethoscopeRheumatologyMagnetic resonance imagingInternal medicinePhysical therapyRadiology

Abstract

fetched live from OpenAlex

These days every article requires disclosure of conflicts. And I have one for this editorial — I am a “physical examination” kind of doctor. Surely that is true of almost all rheumatologists because, despite the advances in ultrasound and magnetic resonance imaging, demonstration of the presence of inflammatory arthritis is still largely based on physical examination. And the usefulness of the physical examination is not limited to rheumatology. The techniques developed by René Laennec in part for his newly invented stethoscope (whispered pectoriloquy, egophony, and fremitus) along with the technique developed by Leopold Auenbrugger (percussion)1 are highly sensitive and specific for identifying lung infiltrates and effusions2. A seasoned examiner can diagnose aortic insufficiency more accurately than either M-mode or 2-dimensional echocardiogram3. Thus, the physical examination remains alive and well. Sjögren syndrome (SS) is a common problem, perhaps second only to rheumatoid arthritis among conditions that cause an inflammatory arthritis4. It can be considered an autoimmune epithelitis5, and predominately affects the exocrine organs. In fact, patients with primary SS can be conveniently divided … Address correspondence to Dr. H. Scofield, 825 NE 18th St., Oklahoma City, Oklahoma 73104, USA. E-mail: hal-scofield{at}omrf.ouhsc.edu.

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 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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score0.661

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.016
GPT teacher head0.260
Teacher spread0.243 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2018
Admission routes1
Has abstractyes

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