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Orthopedic Prostheses: Is There Any Point in Patch Testing?

2004· article· en· W2048844335 on OpenAlexvenueno aff
Mark D.P. Davis, Christen M. Mowad, Pamela L. Scheinman

Bibliographic record

VenueDermatitis · 2004
Typearticle
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOrthopedic surgeryPatch testingContact dermatitisDermatologyGeneral surgeryDentistrySurgeryAllergy

Abstract

fetched live from OpenAlex

The aging of our population and the availability of new medical technologies have contributed to tremendous growth in the number of patients with implanted orthopedic and other devices. As experts on contact dermatitis, we are periodically asked to evaluate patients who have a history of metal allergy prior to surgery. We are sometimes faced with patients who have experienced complications after implant surgery or (more rarely) who have developed skin disease temporally related to surgery. To address these controversial issues, we asked three experts to discuss the role of patch testing in regard to patients with orthopedic implants. Mark D.P. Davis, MD, is an Associate Professor in the Department of Dermatology, Mayo Clinic, Rochester, MN; Christen M. Mowad, MD, is Assistant Professor of Dermatology, Geisinger Medical Center, Danville, PA; and Pamela Scheinman, MD, is Director of the Contact Dermatitis and Occupational Dermatology Unit and Assistant Professor of Dermatology, Tufts-New England Medical Center, Boston, MA.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.970

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)0.0010.000

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 head0.018
GPT teacher head0.252
Teacher spread0.234 · 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 designObservational
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

Citations12
Published2004
Admission routes1
Has abstractyes

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