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Record W3139132142 · doi:10.1128/jcm.03161-20

Evaluation of Diagnostic Accuracy of Eight Commercial Assays for the Detection of Measles Virus-Specific IgM Antibodies

2021· article· en· W3139132142 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Clinical Microbiology · 2021
Typearticle
Languageen
FieldMedicine
TopicParvovirus B19 Infection Studies
Canadian institutionsUniversity of CalgaryAlberta Hospital EdmontonUniversity of AlbertaUniversity of ManitobaPublic Health Agency of Canada
Fundersnot available
KeywordsRubellaMeaslesMeasles virusMedicineVirologyImmunoglobulin MImmunoassayAntibodyImmunologyImmunoglobulin GVaccination

Abstract

fetched live from OpenAlex

= 187) were collected from individuals presenting with other fever and rash illnesses. A total of 7 ELISA kits (Euroimmun native antigens and recombinant nucleoprotein, IBL, Clin-Tech Microimmune, NovaTec NovaLisa, Serion, and Siemens Enzygnost) and one CLIA method (DiaSorin LIAISON XL) were evaluated. The ELISA kits included two IgM capture methods and five indirect methods. Calculated sensitivities and specificities ranged from 75.0% to 98.1% and 86.6% to 99.5%, respectively. The parvovirus B19 IgM positive sera were noted to cause false-positive results, particularly for the ELISA kits from Serion and NovaLisa; specificities for this subset of samples ranged from 51.4% to 100.0%. The capture IgM ELISA methods provided the best combination of sensitivity and specificity.

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.

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)0.006
metaresearch head score (Gemma)0.045
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.045
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.226
GPT teacher head0.471
Teacher spread0.245 · 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