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Record W4415431846 · doi:10.1111/jdv.70139

International insights into bullying in patients with atopic dermatitis: Global trends and key predictors

2025· letter· en· W4415431846 on OpenAlexaff
Roni P. Dodiuk‐Gad, Roberto Takaoka, L. Misery, Jerry Tan, Chaoying Gu, Thomas A. Luger, Flavia Pretti Aslanian, Cita Rosita Sigit Prakoeswa, Ann’Laure Demessant Flavigny, Caroline Le Floc'hc, Nabil Kerrouche, Stéphanie Mérhand, Wendy Smith Begolka, África Luca de Tena Smith, Shulamit Burstein, Delphine Kérob, C. Taïeb, Charbel Skayem, Bruno Halioua, Therdpong Tempark, Abraham Getachew Kelbore, Julien Sénéschal, Alexander J. Stratigos, Martin Steinhoff, Jonathan I. Silverberg

Bibliographic record

VenueJournal of the European Academy of Dermatology and Venereology · 2025
Typeletter
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsWindsor Clinical ResearchWestern UniversityUniversity of Toronto
Fundersnot available
KeywordsAtopic dermatitisObservational studyRepresentativeness heuristicTelephone interviewHuman factors and ergonomicsOccupational safety and healthPopulationInjury preventionSuicide preventionPoison control

Abstract

fetched live from OpenAlex

International audience

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.007
GPT teacher head0.242
Teacher spread0.235 · 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 designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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