Multi-site, multi-country evaluation of analytical and operational performance of a low-mid volume chemiluminescent immunoassay analyzer.
Bibliographic record
Abstract
BACKGROUND: A new automated immunoassay low-mid volume (< or = 250 immunoassays/day) chemiluminescent analyzer, Abbott Architect i1000sR, was evaluated by seven laboratories around the world (4 in Europe, one each in Canada, Japan, and the U.S.A.) to demonstrate equivalent performance for key operating characteristics (e.g., precision, turn around time, limit of detection, functional sensitivity, and linearity). METHODS: The laboratories followed standard protocols to assess precision, limit of detection (LoD), functional sensitivity, assay linearity, method comparison, and sample carryover. Turn around time for three stat assays (beta-hCG, BNP, and CK-MB) and the time required to complete workloads of 50 and 100 tests with a mixture of 75% routine tests and 25% stat tests was also evaluated. RESULTS: Total precision was typically < 5% CV for nine immunoassays. Analytical performance met design goals and demonstrated equivalency to package insert data for assays on market and in use for an existing high volume immunoassay system. Stat turn around times were consistent with the fixed analytical time of 15.6 minutes and met the expectations of the laboratories. Measured test throughput ranged from 47 - 54 tests per hour and demonstrated that the analyzer was fit for the intended purpose of supporting a laboratory that performs < or = 250 immunoassays per day. CONCLUSIONS: A multisite, international analyzer familiarization study is a practical means of confirming that a new instrument meets both a manufacturer's design specifications and users' real world expectations and provides a pragmatic test for the system. The experience of investigators at seven sites around the world indicates that a new fully automated chemiluminescent system is suitable for use.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".