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Record W4408544491 · doi:10.1039/d4cp04794j

<i>In silico</i> screening of photostabilizing reagents for cyanine-based single molecule fluorescence

2025· article· en· W4408544491 on OpenAlexafffund
Jorge Ramos-Sánchez, Yasser Gidi, Terri C. Lovell, Liam Payne, Aya Sakaya, Gonzalo Cosa

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2025
Typearticle
Languageen
FieldChemistry
TopicClick Chemistry and Applications
Canadian institutionsUniversity of TorontoMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsUniversities Space Research AssociationCanadian Institutes of Health ResearchFonds de recherche du Québec – Nature et technologiesClinical Trials Fund, Canadian Institutes of Health Research
KeywordsCyanineIn silicoFluorescenceChemistryCombinatorial chemistryReagentMoleculeOrganic chemistryBiochemistryPhysics

Abstract

fetched live from OpenAlex

acquired through transient absorption spectroscopy. The correlation function then enables screening of the photostabilizing potential of untested reagents from a kinetic standpoint. A new compound, glyceryl monothioglycolate (GMTG), was thus identified. SMF studies show the effectiveness of GMTG as a domestic use, non-toxic, non-volatile alternative to the widely utilized β-mercaptoethanol. Altogether, a predictive model is proposed toward discovering photostabilizers to achieve single molecule fluorescence experiments with enhanced photo- and signal stability.

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 categoriesMeta-epidemiology (narrow)
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 score0.016
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.020
GPT teacher head0.279
Teacher spread0.260 · 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.

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
Published2025
Admission routes2
Has abstractyes

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