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Record W2967898800 · doi:10.1364/prj.7.001042

Simultaneous dual-contrast three-dimensional imaging in live cells via optical diffraction tomography and fluorescence

2019· article· en· W2967898800 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhotonics Research · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsUniversité Laval
FundersAustralian Research CouncilGovernment of Guangdong ProvinceScience, Technology and Innovation Commission of Shenzhen MunicipalityNational Natural Science Foundation of ChinaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsContrast (vision)OpticsFluorescenceMonte Carlo methodMaterials scienceScatteringSIGNAL (programming language)Fluorescence-lifetime imaging microscopyTomographyPhysicsComputer scienceMathematics

Abstract

fetched live from OpenAlex

We report a dual-contrast method of simultaneously measuring and visualizing the volumetric structural information in live biological samples in three-dimensional (3D) space. By introducing a direct way of deriving the 3D scattering potential of the object from the synthesized angular spectra, we obtain the quantitative subcellular morphology in refractive indices (RIs) side-by-side with its fluorescence signals. The additional contrast in RI complements the fluorescent signal, providing additional information of the targeted zones. The simultaneous dual-contrast 3D mechanism unveiled interesting information inaccessible with previous methods, as we demonstrated in the human immune cell (T cell) experiment. Further validation has been demonstrated using a Monte Carlo model. (C) 2019 Chinese Laser Press.

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.

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)0.001
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 score0.043
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.309
Teacher spread0.299 · 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