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Record W4389496437 · doi:10.1039/d3an01855e

Simultaneous quantitation of urinary albumin and creatinine for rapid clinical albuminuria diagnostics using high-throughput paper spray mass spectrometry

2023· article· en· W4389496437 on OpenAlexafffund
Igor Pereira, Jason L. Robinson, Chris G. Gill

Bibliographic record

VenueThe Analyst · 2023
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicForensic Toxicology and Drug Analysis
Canadian institutionsUniversity of VictoriaSimon Fraser UniversityHealth PEIVancouver Island University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAlbuminuriaCreatinineUrineUrologyAlbuminRenal functionChromatographyChemistryCoefficient of variationMedicineInternal medicine

Abstract

fetched live from OpenAlex

= 0.9744 was achieved between the PS-MS results and validated clinical method results. This work demonstrates the utility of PS-MS to simultaneously quantify a large (albumin) and a small (creatinine) molecule directly in patient urine samples, and its potential as a tool for clinical albuminuria diagnostics.

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 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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.538
Threshold uncertainty score0.762

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.130
GPT teacher head0.467
Teacher spread0.336 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations7
Published2023
Admission routes2
Has abstractyes

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