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Record W4280616398 · doi:10.1117/12.2607778

Handheld Point-of-Care Device for the Quantification of Anti-SARS-CoV-2 Antibodies

2022· article· en· W4280616398 on OpenAlexaff
Damber Thapa, Nakisa Samadi, Nima Tabatabaei

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsYork University
Fundersnot available
KeywordsPoint of carePoint-of-care testingMedicineSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)VaccinationAntibodyCoronavirus disease 2019 (COVID-19)Mobile devicePopulationAntibody responseVirologyImmunologyComputer scienceInternal medicinePathologyDisease

Abstract

fetched live from OpenAlex

Antibodies that are produced following infection due to the SARS-CoV-2 virus or vaccination are critical for monitoring the immune response of an individual or the impact of the vaccine over time. As vaccines become available, there is a need for rapid, accurate, and low-cost point-of-care tools for monitoring the effectiveness of the vaccines over time at the population level. Here, we report the efficiency of a handheld point-of-care thermo-photonic device for quantifying anti-SARS-CoV-2 antibodies in humanized control positive solution. Results showed that the imager in conjunction with rapid diagnostic tests (RDT) can detect and quantify antibody levels within clinically relevant range and with a limit of detection of 0.1 µg/ml.

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 score0.103
Threshold uncertainty score0.147

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 head0.034
GPT teacher head0.274
Teacher spread0.240 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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