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Record W4281773944 · doi:10.1016/j.plabm.2022.e00286

Three-year monitoring and comparison of results from two identical blood gas analyzers

2022· article· en· W4281773944 on OpenAlexaff
Huang Yun, Robert J. Dean, Yvonne Dubbelman, Anne Vincent, Ying-pui Michael Chan

Bibliographic record

VenuePractical Laboratory Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsKingston Health Sciences CentreQueen's University
Fundersnot available
KeywordsSpectrum analyzerAnalyteChromatographyGas analyzerpCO2CartridgeChemistryAnalytical Chemistry (journal)Biomedical engineeringMaterials scienceMedicineComputer scienceInternal medicineEnvironmental chemistry

Abstract

fetched live from OpenAlex

Measurement comparability between blood gas analyzers within a laboratory is of utmost importance. This study analyzed the data obtained from a three-year period. For quality monitoring one blood sample was tested on two identical blood gas analyzers at each of three shifts/day for three years. Deming regression analysis was used to determine result correlation and statistical identity between the two analyzers for pH, pCO2, pO2, sodium, potassium, chloride, ionized calcium, glucose, and lactate. Failures in the two-analyzer comparison were determined by the performance limits from the Institute of Quality Management in Healthcare (IQMH) and from the manufacturer respectively. Correlation coefficients were greater than 0.96 (0.9622–0.9975) for all tested analytes. The measurements of every analyte on both analyzers were statistically identical. In the two-analyzer comparison failure numbers/1000 tests for pO2 and glucose varied with the performance limits (IQMH: 0.6 and 49.2; the manufacturer: 19.3 and 4.4, respectively). In addition, persistent glucose failures (>5/week) between the two analyzers occurred occasionally. Results of all tested analytes between the two blood gas analyzers were interchangeable. Recurring glucose discrepancies might be a result of different lots of cartridges used on each analyzer, which were not identified during the initial installation.

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)0.023
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.096
GPT teacher head0.441
Teacher spread0.345 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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