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Record W2919885080 · doi:10.1117/12.2510511

Investigation of the thermal properties of biological cells using a frequency domain photoacoustic microscope

2019· article· en· W2919885080 on OpenAlexaff
Krishnan Sathiyamoorthy, Michael C. Kolios

Bibliographic record

VenuePhotons Plus Ultrasound: Imaging and Sensing 2019 · 2019
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsToronto Metropolitan UniversitySt. Michael's Hospital
Fundersnot available
KeywordsPhotoacoustic imaging in biomedicineMaterials scienceMicroscopeThermalFrequency domainMicroscopyOpticsOptoelectronicsComputer sciencePhysicsComputer vision

Abstract

fetched live from OpenAlex

A photoacoustic sensor for studying the thermal properties of a single biological cell was developed. The sensor used an aluminium foil for heating the sample which enables the study of unstained samples. The PA sensor was developed to work in the heat transmission mode configuration by positioning the detector at the opposite side with respect to heated side of the sample. Rosencwaig’s theoretical model for an open PA cell configuration functional in a heat transmission mode was applied to study the thermal diffusivity of biological cells. MCF7 cells were used in this studied. We measured the thermal diffusivity of 3 cells using the sensor. The average measured thermal diffusivity of MCF7 cells was 0.05 mm<sup>2</sup>/s. The PA sensor allows the spatial mapping of the cell thermal diffusivity and can be used to measure thermal properties of cells in various phases of the cell cycle. It can also be used to measure the effective properties of cells when they have internalized various sensors (e.g. plasmonic nanoparticles).

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)0.000
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 score0.067
Threshold uncertainty score0.809

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 studies0.0000.000
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 head0.013
GPT teacher head0.191
Teacher spread0.178 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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