Genetics of Psoriasis and Psoriatic Arthritis: A Report from the GRAPPA 2010 Annual Meeting: Figure 1.
Bibliographic record
Abstract
Psoriasis vulgaris (PsV) and psoriatic arthritis (PsA) are interrelated disorders, PsA representing a disease within a disease. From an epidemiological perspective, the genetic contributions of PsV and PsA are now well documented. HLA-C is firmly established as a PsV/PsA gene, with HLA-Cw*0602 as a major risk allele. Fine-mapping studies within the MHC region in PsV and PsA have identified novel loci that are independent of the HLA-Cw6 allele. Recent genome-wide association scans have led to a substantial increase in the number of candidate genes reaching genome-wide significance in PsV and PsA cohorts. Most of these genes can be grouped into an integrated pathogenic model of PsV/psoriatic disease comprising distinct signaling networks affecting skin barrier function (LCE3, DEFB4, GJB2), innate immune responses involving nuclear factor-κB and interferon signaling (TNFAIP3, TNIP1, NFKBIA, REL, FBXL19, TYK2, NOS2), and adaptive immune responses involving CD8 T lymphocytes and interleukin 23 (IL-23)/IL-17-mediated lymphocyte signaling (HLA-C, IL12B, IL23R, IL23A, TRAF3IP2, ERAP1). Further development of a global genetic risk score and inclusion of potential gene/gene and gene/environment interactions will likely enhance the predictive value of recently identified genetic variants.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".