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Record W3011589137 · doi:10.1364/boe.390410

Functional optical coherence tomography and photoacoustic microscopy imaging for zebrafish larvae

2020· article· en· W3011589137 on OpenAlexaff
Richard Haindl, Abigail J. Deloria, Caterina Sturtzel, Harald Sattmann, Wolfgang Rohringer, Balthasar Fischer, Marco Andreana, Angelika Unterhuber, Thorsten Schwerte, Martin Distel, Wolfgang Drexler, Rainer A. Leitgeb, Mengyang Liu

Bibliographic record

VenueBiomedical Optics Express · 2020
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsInstitute of Cancer Research
FundersH2020 LEIT Information and Communication TechnologiesFP7 Information and Communication TechnologiesH2020 Leadership in Enabling and Industrial TechnologiesNational Institutes of HealthHorizon 2020 Framework ProgrammeÖsterreichische Forschungsförderungsgesellschaft
KeywordsOptical coherence tomographyPreclinical imagingFunctional imagingPhotoacoustic tomographyBiomedical engineeringPhotoacoustic imaging in biomedicineOptical imagingDiffuse optical imagingModality (human–computer interaction)OpticsMicroscopyTomographyMaterials scienceIn vivoComputer scienceMedicineRadiologyArtificial intelligenceBiologyPhysics

Abstract

fetched live from OpenAlex

We present a dual modality functional optical coherence tomography and photoacoustic microscopy (OCT-PAM) system. The photoacoustic modality employs an akinetic optical sensor with a large imaging window. This imaging window enables direct reflection mode operation, and a seamless integration of optical coherence tomography (OCT) as a second imaging modality. Functional extensions to the OCT-PAM system include Doppler OCT (DOCT) and spectroscopic PAM (sPAM). This functional and non-invasive imaging system is applied to image zebrafish larvae, demonstrating its capability to extract both morphological and hemodynamic parameters in vivo in small animals, which are essential and critical in preclinical imaging for physiological, pathophysiological and drug response studies.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.221
Teacher spread0.210 · 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
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

Citations48
Published2020
Admission routes1
Has abstractyes

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