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Record W1989151318 · doi:10.1002/elps.200600061

Automated screening using microfluidic chip‐based PCR and product detection to assess risk of BK virus‐associated nephropathy in renal transplant recipients

2006· article· en· W1989151318 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.

Bibliographic record

VenueElectrophoresis · 2006
Typearticle
Languageen
FieldMedicine
TopicPolyomavirus and related diseases
Canadian institutionsProvincial Laboratory of Public HealthUniversity of Alberta
Fundersnot available
KeywordsBK virusMicrofluidic chipRenal transplantVirologyNephropathyMedicineMicrofluidicsInternal medicineKidney transplantationTransplantationNanotechnologyMaterials scienceDiabetes mellitus

Abstract

fetched live from OpenAlex

The cost-effective detection of viral particles in bodily fluids could enable more effective responses to viral outbreaks, whether isolated clinical cases, or influenza epidemics. In renal transplant recipients, complications arising from high levels of BK virus can lead to graft dysfunction, graft loss, and/or reduced patient survival. We describe a microfluidic system for the sensitive analysis of BK virus (viral load) in unprocessed urine samples that are applied directly onto the chip, thus avoiding labor-intensive processing and sources of inter-assay variability. Integration of small volume genetic amplification (PCR) and electrophoretic analysis detects as few as 1-2 viral copies, distinguishes between high, medium and low levels of virus and reliably identifies viral loads requiring clinical intervention. As a first step to wider application in the clinic and in the field, the present work presents an entirely microchip-based system, validated against conventional clinical methods using clinical samples.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.349
Threshold uncertainty score0.801

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.015
GPT teacher head0.254
Teacher spread0.239 · 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