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Record W3134999184 · doi:10.1111/jocd.14054

The importance of palpation in the skin cancer screening examination

2021· article· en· W3134999184 on OpenAlexaff
Benjamin G. Gorman, Jennifer M. Hanson, Nahid Y. Vidal

Bibliographic record

VenueJournal of Cosmetic Dermatology · 2021
Typearticle
Languageen
FieldMedicine
TopicNonmelanoma Skin Cancer Studies
Canadian institutionsSKiN Health
Fundersnot available
KeywordsPalpationMedicineBiopsySkin cancerDermatologyPhysical examinationSkin biopsyScarsCancerPerineural invasionSurgeryRadiologyInternal medicine

Abstract

fetched live from OpenAlex

With the recent unprecedented shift toward contactless healthcare solutions, providers should recall the value that proper palpation adds to dermatologic practice. We present a case that demonstrates the limitations of touchless care and how proper palpation during skin cancer examinations may impact cosmetic outcomes. Our patient is an 86-year-old male patient with Sezary syndrome and monoclonal B-cell lymphocytosis whose squamous cell carcinoma invasion was missed by visual inspection alone. He delayed treatment of his biopsy-proven squamous cell carcinoma for 15 months. On follow-up, visual examination only showed a well-healed biopsy scar, and treatment was delayed another 2 months. Finally, thorough physical examination found perineural invasion. This helped guide the Mohs approach, but due to the delays resulted in a larger final defect and poorer cosmetic outcomes. Proper, deep palpation of skin lesions, especially prior biopsy sites, is imperative to the treatment of skin cancer in cosmetically sensitive areas. Biopsy scars on the face often heal well, and visual only inspection may miss crucial details. This case also reminds dermatologists of the importance of patient education in the prompt treatment of skin cancer for the best cosmetic outcomes.

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)0.001
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 score0.055
Threshold uncertainty score0.146

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.024
GPT teacher head0.325
Teacher spread0.301 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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