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Record W4242301837 · doi:10.32920/14638476.v1

High-frequency Ultrasound Scattering from Microspheres and Single Cells

2021· preprint· en· W4242301837 on OpenAlexafffund
Ralph E. Baddour, Michael D. Sherar, J. W. Hunt, G. J. Czarnota, Michael C. Kolios

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
FundersUniversity of TorontoCanadian Institutes of Health ResearchOntario Innovation Trust
KeywordsBackscatter (email)ScatteringTransfer functionMaterials scienceMicrosphereOpticsLight scatteringHomogeneousRange (aeronautics)Computational physicsPhysicsBiological systemAcousticsStatistical physicsComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

Assessing the proportion of biological cells in a volume of interest undergoing structural changes, such as cell death, using high-frequency ultrasound~20–100 MHz!, requires the development of a theoretical model of scattering by any arbitrary cell ensemble. A prerequisite to building such a model is to know the scattering by a single cell in different states. In this paper, a simple model for the high-frequency acoustic scattering by one cell is proposed. A method for deducing the backscatter transfer function from a single, subresolution scatterer is also devised. Using this method, experimental measurements of backscatter from homogeneous, subresolution polystyrenemicrospheres and single, viable eukaryotic cells, acquired across a broad, continuous range of frequencies were compared with elastic scattering theory and the proposed cell scattering model, respectively. The resonant features observed in the backscatter transfer function of microspheres were found to correspond accurately to theoretical predictions. Using the spacing of the major spectral peaks in the transfer functions obtained experimentally, it is possible to predict microsphere diameters with less than 4% error. Such good agreement was not seen between the cell model and the measured backscatter from cells. Possible reasons for this discrepancy are discussed

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.037
Threshold uncertainty score1.000

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)0.0010.000

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 head0.009
GPT teacher head0.186
Teacher spread0.177 · 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.

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

Citations13
Published2021
Admission routes2
Has abstractyes

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