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Metrics and definitions used in the assessment of cognitive impairment in systemic lupus erythematosus: A systematic review

2021· review· en· W3171352680 on OpenAlexaff
Kimberley Yuen, Robin Green, Kathleen Bingham, Lesley Ruttan, Victoria Lee‐Kim, Maria Carmela Tartaglia, Melanie Anderson, Moe Zandy, May Y. Choi, Marvin J. Fritzler, Joan Wither, Dorcas Beaton, Patricia Katz, Zahi Touma

Bibliographic record

VenueSeminars in Arthritis and Rheumatism · 2021
Typereview
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsUniversity of CalgaryInstitute for Work & HealthToronto Western HospitalToronto Rehabilitation InstituteUniversity of TorontoUniversity Health NetworkQueen's University
Fundersnot available
KeywordsMedicinePsycINFOMEDLINESystemic lupus erythematosusCINAHLInternal medicinePsychological interventionPsychiatry

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)0.025
metaresearch head score (Gemma)0.099
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.025
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.099
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0190.017
Bibliometrics0.0200.020
Science and technology studies0.0010.002
Scholarly communication0.0050.004
Open science0.0030.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.050
GPT teacher head0.361
Teacher spread0.311 · 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 designSystematic review
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

Citations24
Published2021
Admission routes1
Has abstractno

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