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Record W1932874225 · doi:10.1063/1.4738962

Robust and economical multi-sample, multi-wavelength UV/vis absorption and fluorescence detector for biological and chemical contamination

2012· article· en· W1932874225 on OpenAlexaff
Peter J. Lu, Melanie M. Hoehl, James B. Macarthur, Peter A. Sims, Hongshen Ma, Alexander H. Slocum

Bibliographic record

VenueAIP Advances · 2012
Typearticle
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDetectorContaminationAbsorption (acoustics)Ethylene glycolFluorescenceActivity-based costingRobustness (evolution)Environmental scienceMaterials scienceComputer scienceChemistryOpticsTelecommunicationsPhysicsBusiness

Abstract

fetched live from OpenAlex

We present a portable multi-channel, multi-sample UV/vis absorption and fluorescence detection device, which has no moving parts, can operate wirelessly and on batteries, interfaces with smart mobile phones or tablets, and has the sensitivity of commercial instruments costing an order of magnitude more. We use UV absorption to measure the concentration of ethylene glycol in water solutions at all levels above those deemed unsafe by the United States Food and Drug Administration; in addition we use fluorescence to measure the concentration of d-glucose. Both wavelengths can be used concurrently to increase measurement robustness and increase detection sensitivity. Our small robust economical device can be deployed in the absence of laboratory infrastructure, and therefore may find applications immediately following natural disasters, and in more general deployment for much broader-based testing of food, agricultural and household products to prevent outbreaks of poisoning and disease.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score0.404

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 head0.036
GPT teacher head0.243
Teacher spread0.206 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

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