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Record W2018995538 · doi:10.1177/0961203313503914

Reflections on Lupus 2013: butterflies, wolves and prophecies

2013· review· en· W2018995538 on OpenAlexaffabout
Fritzler Mj

Bibliographic record

VenueLupus · 2013
Typereview
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAutoantibodyMedicineSystemic lupus erythematosusImmunologyEnvironmental ethicsPathologyDiseaseAntibody

Abstract

fetched live from OpenAlex

The recently concluded Tenth International Congress on Systemic Lupus Erythematosus (SLE) held in Buenos Aires was a resounding success. This overview summarizes some of the origins of the First International Congress held in Calgary, Canada in 1986, predictions offered by past Congress Presidents, and a perspective on the trends in autoantibody testing, which remains one of the key approaches to the early and accurate diagnosis of SLE. The last few decades have witnessed a remarkable proliferation of new diagnostic technologies including addressable laser bead immunoassays and, more recently, chemiluminescence and lateral flow technologies that could find a clinical niche in point-of-care diagnostics. Against the backdrop of these constantly emerging technologies, indirect immunofluorescence has remained the platform of choice for many laboratories and diagnosticians. The notion that autoantibodies are pathogenic has been challenged by evidence that some autoantibodies are protective, some may have catalytic capacity while others may be neutral or have no function at all. The latter notion of functionless or "junk" autoantibodies needs to be taken under some advisement, because there was a time when a great proportion of the human genome was considered to include "junk DNA". The butterfly as a symbol of hope and progress in SLE research over the past 27 years since the First International Congress on SLE is almost certainly to be even more appropriate when future Congresses are held in Geneva (2015), Melbourne (2017) and eventually one in 2050.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.477
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.002

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 head0.135
GPT teacher head0.420
Teacher spread0.285 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations3
Published2013
Admission routes2
Has abstractyes

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