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Assessment of Immunoglobulin M Enzyme Immunoassays for Diagnosis of Measles

2003· article· en· W2101372466 on OpenAlexaff
Graham Tipples, R Hamkar, Talat Mohktari-Azad, Michael J. Gray, Geoff Parkyn, Carol Head, Samuel Ratnam

Bibliographic record

VenueJournal of Clinical Microbiology · 2003
Typearticle
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsSt. John’s Health Sciences CentreHealth Canada
Fundersnot available
KeywordsImmunoassayAntibodyMeaslesImmunoglobulin GEnzymeImmunoglobulin MMolecular biologyVirologyChemistryChromatographyBiologyImmunologyBiochemistryVaccination

Abstract

fetched live from OpenAlex

We evaluated the performance of three commercial measles immunoglobulin M enzyme immunoassays from Meddens, Denka Seiken, and Behring. The sensitivities were determined to be 96.7% for the Meddens and Denka Seiken assays and 87.9% for the Behring assay. The specificities of the assays were determined to be 94.6% for Meddens, 98.2% for Denka Seiken, and 98.7% for Behring.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.426

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.066
GPT teacher head0.433
Teacher spread0.368 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations39
Published2003
Admission routes1
Has abstractyes

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