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Record W3191424700 · doi:10.1016/j.jaut.2021.102707

Guideline for the diagnosis, treatment and long-term management of cutaneous lupus erythematosus

2021· article· en· W3191424700 on OpenAlexaff
Qianjin Lu, Hai Long, Steven Chow, Syarief Hidayat, Retno Danarti, Yulianto Listiawan, Danqi Deng, Qing Guo, Hong Fang, Juan Tao, Ming Zhao, Leihong Xiang, Nan Che, Fen Li, Hongjun Zhao, Chak Sing Lau, Fong Cheng Ip, King Man Ho, Arnelfa C Paliza, Vicheth Chan, Kiran Godse, Soyun Cho, Chew Swee Seow, Yoshiki Miyachi, Tran Hau Khang, Rataporn Ungpakorn, Hassan Galadari, Rashmikant Shah, Kehu Yang, Youwen Zhou, Carlo Selmi, Amr H. Sawalha, Xuan Zhang, Yaolong Chen, Chrang‐Shi Lin

Bibliographic record

VenueJournal of Autoimmunity · 2021
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineGuidelineDermatologyVenereologyCutaneous Lupus ErythematosusChecklistLupus erythematosusIntensive care medicineFamily medicinePathologyImmunology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.003
metaresearch head score (Gemma)0.008
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: Editorial · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0040.001
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0080.008

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 head0.046
GPT teacher head0.348
Teacher spread0.302 · 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
GenreEditorial

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

Citations81
Published2021
Admission routes1
Has abstractno

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