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Record W4323652368 · doi:10.4155/bio-2022-0242

Method development for the quantification of lead levels in whole blood sampled on Mitra <sup>®</sup> with VAMS <sup>®</sup> tips by inductively coupled plasma–MS/MS

2023· article· en· W4323652368 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBioanalysis · 2023
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsUniversité du Québec à Trois-RivièresInstitut National de Santé Publique du Québec
Fundersnot available
KeywordsVenipunctureBlood samplingLead (geology)Sampling (signal processing)Whole bloodChemistryComputer scienceMedicineSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Background: Lead is harmful for humans by having adverse effects on different biological systems. Venepuncture is the gold standard for blood lead level analysis, but this method has many flaws. The goal of this research was to develop and validate a more practical approach for blood sampling. Materials & methods: Mitra® devices based on VAMS® and inductively coupled plasma–MS/MS technologies were employed. Performance evaluation of the newly developed method was also performed by comparing it versus a commonly used method at the Centre de Toxicologie du Québec for blood lead level analysis. Results: Comparison showed no signs of significant difference between the two methods. Conclusion: VAMS may be a useful alternative sampling approach for further research on blood lead analysis and possibly for many other trace elements.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.174
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.071
GPT teacher head0.316
Teacher spread0.245 · 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