MétaCan
Menu
Back to cohort

Recent advances in managing and understanding pyoderma gangrenosum

2019· preprint· en· W2995668137 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueF1000Research · 2019
Typepreprint
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsPyoderma gangrenosumNeutrophilic dermatosisMedicineIntensive care medicinePresentation (obstetrics)PathophysiologyClinical trialBioinformaticsDiseasePathologySurgeryBiology

Abstract

fetched live from OpenAlex

Pyoderma Gangrenosum (PG) is a rare neutrophilic dermatosis with multiple different clinical presentations and associated comorbidities. PG has historically been a challenging disorder to diagnose, leading to the development of new diagnostic criteria rather than the traditional approach of a diagnosis of exclusion. The pathophysiology is thought to involve both innate and adaptive immune system dysregulation, neutrophilic abnormalities, environmental, and genetic factors. As of today, no gold standard therapy exists for the treatment of PG, and the literature is restricted to mainly case reports, case series, and 2 small randomized clinical trials. Topical, systemic, and biologic therapy, as well as adequate analgesia and proper wound care all play a role in the management of PG. Recent studies have identified additional cytokines and signalling cascades thought to be involved in the pathogenesis of PG, ultimately leading to the development of new targeted therapies. This review will focus on recent advances in the pathophysiology, clinical presentation and associated comorbidities, diagnosis, and management of PG.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.740
Threshold uncertainty score0.933

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.071
GPT teacher head0.360
Teacher spread0.289 · 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