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Record W4403097517 · doi:10.1364/josaa.534150

Visualizing the fine structure and dynamics of living cells with temporal polychromatic digital holographic microscopy

2024· article· en· W4403097517 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of the Optical Society of America A · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDigital Holography and Microscopy
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationQuébec Consortium for Drug Discovery
KeywordsDigital holographic microscopyHolographyMicroscopyDynamics (music)Computer scienceDigital holographyVisualizationComputer visionOpticsBiological systemSample (material)Artificial intelligencePhysicsBiologyAcoustics

Abstract

fetched live from OpenAlex

Polychromatic digital holographic microscopy (P-DHM) has demonstrated its capacity to generate highly denoised optical path difference images, thereby enabling the label-free visualization of fine cellular structures, such as the dendritic arborization within neuronal cells in culture. So far, however, the sample must remain more or less stationary since P-DHM is performed manually, i.e., all actions are carried out sequentially over several minutes. In this paper, we propose fully automated, robust, and efficient management of the acquisition and reconstruction of the time series of polychromatic hologram sets, transforming P-DHM into temporal P-DHM. Experimental results have demonstrated the ability of the proposed temporal P-DHM implementation to non-invasively and quantitatively reveal the fine structure and dynamics of living 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.

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 score0.135
Threshold uncertainty score0.342

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 studies0.0000.001
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 head0.003
GPT teacher head0.229
Teacher spread0.226 · 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