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Record W3092456836 · doi:10.1111/ijd.15224

Ulcerative versus non‐ulcerative panniculitis: is it time for a novel clinical approach to panniculitis?

2020· review· en· W3092456836 on OpenAlexaff
Eran Shavit, Angelo Valerio Marzano, Afsáneh Alavi

Bibliographic record

VenueInternational Journal of Dermatology · 2020
Typereview
Languageen
FieldMedicine
TopicDermatological and COVID-19 studies
Canadian institutionsWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsPanniculitisMedicineDermatopathologyVasculitisPathologyClinical significanceAdipose tissueDermatologyDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Panniculitis, or inflammation of the fatty tissue, is an ongoing diagnostic challenge to both dermatologists and pathologists. The basis of the current panniculitis classification is histology, whether the inflammation is mainly located in the fibrovascular septa or in the adipose lobules thereafter with or without vasculitis. However, overall, the difficulty rises due to various terminologies and lack of clinical relevance with this classification. In addition to that, the majority of panniculitides have mixed infiltration of both lobular and septal and not a clear-cut distinction. The aim of this article is to provide a novel clinical algorithm to the diagnosis of panniculitis and thus to provide guidelines for all clinicians who may encounter this challenging condition in their clinical practice.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.504
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.184
GPT teacher head0.467
Teacher spread0.282 · 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.

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

Citations9
Published2020
Admission routes1
Has abstractyes

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