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Record W2140438994 · doi:10.1039/c2cp23278b

The development of direct multicolour fluorescence cross-correlation spectroscopy: Towards a new tool for tracking complex biomolecular events in real-time

2011· article· en· W2140438994 on OpenAlexafffund
Holly Wobma, Megan L. Blades, Ekaterina Grekova, Dylan McGuire, Kun Chen, Warren C. W. Chan, David T. Cramb

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsUniversity of TorontoMcGill UniversityUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchCalifornia HIV/AIDS Research Program
KeywordsBiomoleculeFluorescence correlation spectroscopyFluorescenceFluorescence spectroscopyTracking (education)SpectroscopyBiological systemNanotechnologyFluorescence cross-correlation spectroscopyDNAChemistrySIGNAL (programming language)BiophysicsMaterials scienceBiologyComputer sciencePhysicsBiochemistryOptics

Abstract

fetched live from OpenAlex

Direct three-colour fluorescence cross-correlation spectroscopy can reveal interactions between three fluorescently labelled biomolecules, giving insight toward the complex events that constitute signal transduction pathways. Here we provide the optical and theoretical basis for this technology and demonstrate its ability to detect specific biological associations between nanoparticle-labelled DNA molecules.

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 score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.028
GPT teacher head0.316
Teacher spread0.289 · 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

Citations12
Published2011
Admission routes2
Has abstractyes

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