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Record W2097684042 · doi:10.1177/0961203314530485

Lupus – the cold, hard facts

2014· article· en· W2097684042 on OpenAlexaff
NWK Wong, VT-Y Ng, Soha Eldessouki Ibrahim, Marat Slessarev, Vinod Chandran

Bibliographic record

VenueLupus · 2014
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsToronto Western HospitalMcMaster UniversityUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsFrostbiteMedicineSystemic lupus erythematosusVasculitisImmunologyDiseaseAntiphospholipid syndromeDermatologyAntibodyInternal medicineSurgery

Abstract

fetched live from OpenAlex

Systemic lupus erythematosus (SLE) is a multisystem chronic disease with a multitude of clinical presentations. We review and synthesize how an environmental insult (exposure to extreme cold for a short duration) and endogenous (antiphospholipid antibody syndrome, SLE vasculitis) insults in a susceptible young female with lupus (peripheral arterial disease, smoking, SLE) led to a perfect storm resulting in catastrophic injuries (frostbite).

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.002

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 head0.029
GPT teacher head0.277
Teacher spread0.248 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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