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Record W2987320773 · doi:10.1016/j.plabm.2019.e00147

A high-throughput test for diabetes care: An evaluation of the next generation Roche Cobas c 513 hemoglobin A1C assay

2019· article· en· W2987320773 on OpenAlexafffund
Jessica L. Gifford, Trefor Higgins, S.M. Hossein Sadrzadeh

Bibliographic record

VenuePractical Laboratory Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsCalgary Laboratory ServicesUniversity of AlbertaUniversity of CalgaryHealth Sciences Centre
FundersAbbott DiagnosticsAbbott Canada
KeywordsThroughputMedicineHemoglobinDiabetes mellitusInternal medicineBiomedical engineeringComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

The level of glycated hemoglobin A (HbA1C) in blood is the preferred marker for diabetes monitoring and treatment. Here, we evaluate the analytical performance of the Roche Diagnostics Cobas c 513, a stand-alone HbA1C immunoassay analyzer. Performance was assessed with regards to imprecision, accuracy, linearity, method comparison against the Roche Cobas Integra 800 CTS, specimen stability, interference from common hemoglobin variants and hemoglobin F, and throughput. Within-run and between-run precisions were 0.5–0.7 and 0.8–1.3%CV, respectively. An average bias of −1.6% to proficiency survey samples was observed. The c 513 correlated well with the Integra (slope = 0.94, y-intercept = 0.50, and correlation coefficient = 0.998). The effect of hemoglobin variants on this assay was negligible while specimens containing ≥10% HbF demonstrated a negative bias. The c 513 instrument can process up to 340 samples per hour. The c 513 is a precise, accurate, automated high throughput analyzer for measuring HbA1C in large laboratories.

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)0.019
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.106
GPT teacher head0.386
Teacher spread0.280 · 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 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

Citations4
Published2019
Admission routes2
Has abstractyes

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