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Record W1527866765 · doi:10.1109/jphot.2014.2326665

Lensless Miniature Portable Fluorometer for Measurement of Chlorophyll and CDOM in Water Using Fluorescence Contact Imaging

2014· article· en· W1527866765 on OpenAlexafffund
Lior Blockstein, Orly Yadid-Pecht

Bibliographic record

VenueIEEE photonics journal · 2014
Typearticle
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Heritage Foundation for Medical ResearchCanadian Institutes of Health ResearchAsylum, Migration and Integration FundAlberta Innovates - Technology Futures
KeywordsColored dissolved organic matterFluorometerFluorescenceAbsorption (acoustics)Materials scienceOpticsLight-emitting diodeLuminescenceOptoelectronicsAnalytical Chemistry (journal)ChemistryPhysicsChromatography

Abstract

fetched live from OpenAlex

We report on the design, fabrication, and verification of a proof-of-concept miniature fluorometer, which is designed to measure chlorophyll and colored dissolved organic matter (CDOM) concentration in aquatic environment. The system utilizes light emitting diodes (LEDs) for fluorescence excitation and absorption filters for excitation light attenuation. The excitation LED for chlorophyll has peak emission at 465 nm, and the excitation LED for CDOM has peak emission at 341 nm. Our device demonstrates the concept of attaching two different absorption filters on a single sensor array for measuring the fluorescence signal from two different fluorescent dyes. We have tested the system's ability to detect fluorescence from various concentrations of fluorescein as a close simulant and the calibration standard for chlorophyll, and quinine sulfate dihydrate (QSD) as a simulant and calibration standard for CDOM. We have successfully acquired the fluorescent signal for fluorescein between 0.7 and 1000 nM and for QSD between 2.6 and 638 nM.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.021
GPT teacher head0.238
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations28
Published2014
Admission routes2
Has abstractyes

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