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Record W2511801649 · doi:10.1021/acssensors.6b00368

Low-Cost Leukemic Serum Marker Screening Using Large Area Nanohole Arrays on Plastic Substrates

2016· article· en· W2511801649 on OpenAlexafffund
Chiara Valsecchi, Talon Jones, Chen Wang, Hans Lochbihler, J. W. Menezes, Alexandre G. Brolo

Bibliographic record

VenueACS Sensors · 2016
Typearticle
Languageen
FieldEngineering
TopicNanofabrication and Lithography Techniques
Canadian institutionsMount Sinai HospitalUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiosensorMaterials sciencePlasmonNanotechnologyLeukemiaBiomedical engineeringOptoelectronicsMedicineImmunology

Abstract

fetched live from OpenAlex

Plasmonic biosensors, particularly arrays of nanoholes on thin gold films, have been widely explored in recent years as possible platforms for fast medical diagnostic. In this work, we present a screening method for leukemia cancer markers that uses a plasmonic biosensor based on nanohole arrays fabricated on plastic substrates. The low-cost, scalable, and reproducible nanohole array structures were fabricated by UV nanoimprinting technique. The relative concentration of human immunoglobulin kappa and lambda light chains in blood serum was employed as a screening method. The kappa/lambda concentration ratio was used to determine an unbalance in the immunoglobulin production due to leukemia. The platform was tested using serum samples from patients with known leukemia diagnoses. The results indicated that this inexpensive and flexible plasmonic platform is a promising tool for routine screening in clinical settings.

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)0.000
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 score0.051
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.017
GPT teacher head0.229
Teacher spread0.211 · 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 designBench or experimental
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

Citations21
Published2016
Admission routes2
Has abstractyes

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