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Record W2069639056 · doi:10.1117/1.3490641

Forward-collected simultaneous fluorescence lifetime imaging and coherent anti-Stokes Raman scattering microscopy

2011· article· en· W2069639056 on OpenAlexaff
Aaron D. Slepkov, Andrew Ridsdale, Huei-Ning Wan, Ming-Hao Wang, Adrian F. Pegoraro, Douglas J. Moffatt, John Paul Pezacki, Fu‐Jen Kao, Albert Stolow

Bibliographic record

VenueJournal of Biomedical Optics · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSpectroscopy Techniques in Biomedical and Chemical Research
Canadian institutionsQueen's UniversityNational Research Council CanadaSteacie Institute for Molecular Sciences
FundersIndustrial Technology Research InstituteNational Science Council
KeywordsFemtosecondRaman scatteringFluorescence-lifetime imaging microscopyOpticsMaterials scienceMicroscopyPhoton countingMulti-mode optical fiberFluorescenceRaman spectroscopyAutofluorescenceCoherent anti-Stokes Raman spectroscopyLaserOptical fiberPhotonPhysics

Abstract

fetched live from OpenAlex

We demonstrate the simultaneous collection and separation of femtosecond-laser-based forward-collected coherent anti-Stokes Raman scattering (F-CARS) and two-photon-excitation-induced fluorescence lifetime images (FLIM) using time-correlated single photon counting (TCSPC). We achieve this in a nondescanned geometry using a single multimode fiber without significant loss of light, field of view, and most importantly, TCSPC timing fidelity. In addition to showing the ability to separate CARS images from FLIM images using time gating, we also demonstrate composite multimodal epicollected FLIM imaging with fiber-collected F-CARS imaging in live cells.

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)0.001
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 score0.049
Threshold uncertainty score0.591

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.010
GPT teacher head0.288
Teacher spread0.279 · 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

Citations27
Published2011
Admission routes1
Has abstractyes

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