MétaCan
Menu
← Back to cohort
Record W4385239382 · doi:10.55788/9fa1bf2c

Medicom Conference Report Proceedings of the 6th IFPA WPPA Conference

2021· paratext· en· W4385239382 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typeparatext
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
FundersUniversity of TorontoPfizer
KeywordsComputer science

Abstract

fetched live from OpenAlex

Psoriatic arthritis is an inflammatory arthritis that occurs in about a quarter of patients with cutaneous psoriasis and most often begins after the onset of skin disease.PsA is highly heritable, but a greater contribution to disease susceptibility is attributable to psoriasis-associated gene variants.Class I HLA B alleles are most strongly associated with PsA.Several environmental factors, particularly trauma, have been identified as potential triggers of PsA.Recent pathogenetic studies using samples from the synovial fluid, synovium, skin and enthesis indicate the importance of tissue resident memory cells as well as CD8 T cells in disease pathogenesis.γδT-cells play an important role in the enthesis.Anti-cytokine therapies also indicate tissue cytokine hierarchy with IL-23 and IL-17 being important for skin psoriasis, TNF, IL-17and IL-23 for peripheral synovitis, TNF and IL-17 for axial arthritis, IL-17 and IL-12/23 for enthesitis and TNF and IL-12/23 for inflammatory bowel disease.The pathogenesis of PsA is complex with an interplay between genetic and environmental factors leading to aberrant immune activation possibly in the skin, gut or enthesis leading to sustained inflammation in the synovium and periarticular structures, leading to bone loss as well as new-bone formation.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.372
Threshold uncertainty score0.896

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.3720.216

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 head0.424
GPT teacher head0.432
Teacher spread0.009 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicHealth Systems, Economic Evaluations, Quality of Life→French-language works237,207→