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Record W4385922954 · doi:10.1021/acs.analchem.3c00217

<b>Fluorescence Excitation-Emission-Matrix Imaging</b>

2023· article· en· W4385922954 on OpenAlexafffund
Oren Katz, Travis Ferguson, Emma Abbey, Sarah-Johanna Klose, Chris Prüfert, Hans‐Peter Loock

Bibliographic record

VenueAnalytical Chemistry · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsQueen's UniversityUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Victoria
KeywordsChemistryFluorescenceExcitationHadamard transformWavelengthPixelTernary operationOpticsMatrix (chemical analysis)MultiplexingExcitation wavelengthPhysicsTelecommunications

Abstract

fetched live from OpenAlex

We present a 4-dimensional (4D) fluorescence imaging system in which each of the 65,536 pixels in the image array contains an excitation-emission-matrix spectrum with 31 excitation wavelengths and 8 emission wavelengths ( x, y, λ exc, λ em ). Hadamard-transform multiplexing of the excitation light from a 31-channel programmable light source allows for an increase in the data acquisition rate so that each 65,536-pixel image can be obtained within 8 s. The system is demonstrated and characterized using, first, a 4D image of 10 capillaries filled with four dye solutions and their binary and ternary mixtures, and, second, using a sequence of about 100 images of layered fluorescent dye solutions and their changing fluorescence as a function of temperature. Multivariate analysis using parallel factor analysis produces images of the spatial distribution of the fluorophores together with their relative intensity as a function of time.

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 score0.022
Threshold uncertainty score0.799

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 head0.008
GPT teacher head0.317
Teacher spread0.309 · 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

Citations13
Published2023
Admission routes2
Has abstractyes

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