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Record W2954357071 · doi:10.1111/bjd.18309

Defining lesional, perilesional and unaffected skin in hidradenitis suppurativa: proposed recommendations for clinical trials and translational research studies

2019· letter· en· W2954357071 on OpenAlexaff
John W. Frew, Kristina Navrazhina, Angel S. Byrd, Amit Garg, John R Ingram, Joslyn S. Kirby, Michelle A. Lowes, Haley B. Naik, Vincent Piguet, Errol P. Prens

Bibliographic record

VenueBritish Journal of Dermatology · 2019
Typeletter
Languageen
FieldMedicine
TopicHidradenitis Suppurativa and Treatments
Canadian institutionsWomen's College HospitalUniversity of Toronto
FundersNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsHidradenitis suppurativaMedicineDermatologyClinical trialTranslational researchSurgeryPathologyDisease

Abstract

fetched live from OpenAlex

Hidradenitis suppurativa (HS) is a chronic, recurring inflammatory skin condition for which the pathogenesis is not completely elucidated1. With the increase in HS‐related research comes the need to enhance reproducibility, quality and accuracy of scientific methods. Unlike other inflammatory dermatoses such as psoriasis or atopic dermatitis, HS lesions are morphologically diverse and include nodules, abscesses, tunnels and fibrosis in various permutations and combinations admixed in the same anatomical region1. This makes general definitions as ‘lesional’ and ‘non‐lesional’ insufficient for HS‐related investigations. A definition for non‐lesional skin is lacking.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.926
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
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 head0.359
GPT teacher head0.539
Teacher spread0.180 · 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 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

Citations40
Published2019
Admission routes1
Has abstractyes

Explore more

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