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Record W2770873843 · doi:10.1109/ultsym.2017.8091934

Theoretical and experimental investigation of the nonlinear dynamics of nanobubbles excited at clinically relevant ultrasound frequencies and pressures: The role of lipid shell buckling

2017· article· en· W2770873843 on OpenAlexaff
Amin Jafarisojahrood, Lenitza M. Nieves, Christopher Hernandez, Agata A. Exner, Michael C. Kolios

Bibliographic record

Venue2017 IEEE International Ultrasonics Symposium (IUS) · 2017
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsToronto Metropolitan UniversitySt. Michael's Hospital
Fundersnot available
KeywordsMicrobubblesUltrasoundDrug deliveryExcited stateBiomedical engineeringMaterials scienceDynamics (music)BucklingNonlinear systemShell (structure)NanotechnologyAcousticsMedicinePhysicsComposite materialAtomic physics

Abstract

fetched live from OpenAlex

Microbubbles (MBs) excited by ultrasound (Us) are used as contrast agents for the detection of blood vessels. MBs can also be used to enhance drug delivery. However, the usage of MBs is limited to the blood pool due to their large size; where detection of biomarkers on tumor cells and effective drug delivery, requires MBs to reach the tumor tissue outside of the vasculature.

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 score0.176
Threshold uncertainty score0.517

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 science0.0010.000
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 head0.009
GPT teacher head0.240
Teacher spread0.232 · 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

Citations10
Published2017
Admission routes1
Has abstractyes

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