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Record W2325912602 · doi:10.3899/jrheum.130462

Biomarkers: Project Update from the GRAPPA 2012 Annual Meeting

2013· article· en· W2325912602 on OpenAlexvenueno aff
Oliver FitzGerald, Philip J. Mease

Bibliographic record

VenueThe Journal of Rheumatology · 2013
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePsoriatic arthritisIdentification (biology)Protocol (science)Medical physicsPsoriasisAlternative medicinePathologyImmunology

Abstract

fetched live from OpenAlex

For members of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA), an important goal has been the identification of soluble biomarkers in psoriatic arthritis that might predict the development of radiographic progression. Work over the past year has resulted in approval of a draft protocol, and an announcement is forthcoming of the outcome of an assessment process for centers that applied to manage the project. GRAPPA is now ready to commence formal negotiations with potential funding partners and intends to initiate this project in the near future.

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)0.025
metaresearch head score (Gemma)0.036
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 score0.025
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.036
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0090.009
Science and technology studies0.0010.001
Scholarly communication0.0060.005
Open science0.0050.005
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0180.020

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 head0.014
GPT teacher head0.263
Teacher spread0.249 · 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

Citations9
Published2013
Admission routes1
Has abstractyes

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