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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 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.
fundA Canadian funder is recorded on the work.

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.

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)0.004
metaresearch head score (Gemma)0.011
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 score0.366
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.106
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