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Record W4235732203 · doi:10.1177/120347540500900104

Metastatic Basal Cell Carcinoma: Report of Two Cases and Literature Review

2005· article· en· W4235732203 on OpenAlexaff
Patricia T. Ting, Richard Kasper, John P. Arlette

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2005
Typearticle
Languageen
FieldMedicine
TopicNonmelanoma Skin Cancer Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineBasal cell carcinomaDermatologyIncidence (geometry)CarcinomaDiseaseRadiologyPathologySurgeryBasal cell

Abstract

fetched live from OpenAlex

Background: Metastatic basal cell carcinoma (MBCC) is defined as primary cutaneous basal cell carcinoma (BCC) that spreads to distant sites as histologically similar metastatic deposits of BCC. There are less than 300 reported cases of MBCC in the literature. Methods: This article examines two cases of MBCC and provides a literature review of risk factors inherent in epidemiology, patient demographics, and the clinicohistopathological characteristics of primary and metastatic BCC lesions. Results: MBCC is a rare complication of BCC with high morbidity and mortality rates. Patients with MBCC often begin with long-standing primary BCC lesions that are either large or recurrent after treatment. Cases of MBCC have a higher incidence of the more aggressive histologic patterns (morpheic, infiltrating, metatypical, and basosquamous). Perineural space invasion may be an indicator of aggressive disease. Metastases often involve regional lymph nodes, lungs, bone, and skin. Conclusion: These case reports and review provide important diagnostic and management considerations for primary BCC and MBCC. Early intervention with aggressive treatment measures may improve the prognosis and survival of MBCC patients.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.004
Science and technology studies0.0030.002
Scholarly communication0.0030.003
Open science0.0030.003
Research integrity0.0070.003
Insufficient payload (model declined to judge)0.0050.005

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 head0.030
GPT teacher head0.310
Teacher spread0.280 · 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 designCase report
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

Citations70
Published2005
Admission routes1
Has abstractyes

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