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Record W2755292473 · doi:10.1111/exd.13445

Proceeding report of the Symposium on Hidradenitis Suppurativa Advances (<scp>SHSA</scp>)

2017· article· en· W2755292473 on OpenAlexaff
Ali Mehdizadeh, Afsáneh Alavi, Raed Alhusayen, Boris Bauer, Falk G. Bechara, Marc Bourcier, Alain Brassard, Vahid Djamei, Jan Dutz, Ralph George, Mondana Ghias, Melinda Gooderham, Iltefat Hamzavi, Lauren Hoffman, Angela Yung Chi Hou, Howard Hu, Alexa B. Kimball, Mark G. Kirchhof, Darya Kryzskaya, Maria del Carmen Liy Wong, Michelle A. Lowes, Charles Lynde, Chelsea McLellen, Errol P. Prens, Lisette M. Prens, Tetyana Rogalska, R. Gary Sibbald, Mia Sisic, Marcus G. Tan, Dennis Wong

Bibliographic record

VenueExperimental Dermatology · 2017
Typearticle
Languageen
FieldMedicine
TopicHidradenitis Suppurativa and Treatments
Canadian institutionsHospital for Sick ChildrenMcGill UniversityUniversity of OttawaUniversity of AlbertaHealth Sciences CentreSunnybrook Health Science CentreWomen's College HospitalToronto General HospitalSKiN HealthUniversity of British ColumbiaPublic Health OntarioUniversity of WindsorMoncton HospitalMontreal Children's HospitalUniversity of Toronto
Fundersnot available
KeywordsHidradenitis suppurativaMedicineEpidemiologyQuality of life (healthcare)DiseaseDermatologyPathologyNursing

Abstract

fetched live from OpenAlex

Hidradenitis Suppurativa (HS) is a chronic debilitating skin condition that impairs the productivity and the quality of patients` lives. HS has recently drawn lots of attention among scholars to further expand their knowledge but it still loads with uncertainties and gaps to be explored. This publication addresses these uncertainties, and provides a road-map for researchers, scholars and clinicians from different disciplines for their future studies about HS. This is a proceeding report of the first Symposium on Hidradenitis Suppurativa Advances (SHSA), and it reviews the scientific sessions about the epidemiology, pathophysiology, presentations, and management of HS. This symposium was a great opportunity for experts in the HS field to exchange their knowledge, and improve their mutual understanding of this disease.

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)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.045
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0450.014

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 head0.018
GPT teacher head0.319
Teacher spread0.300 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations6
Published2017
Admission routes1
Has abstractyes

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