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Record W2905757330 · doi:10.1039/c8nr08763f

Sink or float? Characterization of shell-stabilized bulk nanobubbles using a resonant mass measurement technique

2018· article· en· W2905757330 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.

Bibliographic record

VenueNanoscale · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMinerals Flotation and Separation Techniques
Canadian institutionsToronto Metropolitan UniversityToronto Public Health
FundersDOD Prostate Cancer Research ProgramNational Institute of Biomedical Imaging and BioengineeringNational Institutes of HealthNational Foundation for Cancer ResearchU.S. Department of Defense
KeywordsBubbleCharacterization (materials science)Sink (geography)Float (project management)Materials scienceShell (structure)MechanicsChemical physicsNanotechnologyComputational physicsPhysicsComposite materialMarine engineeringEngineering

Abstract

fetched live from OpenAlex

Nano-sized shell-stabilized gas bubbles have applications in various fields ranging from environmental science to biomedical engineering. A resonant mass measurement (RMM) technique is demonstrated here as a new and only method capable of simultaneously measuring the size and concentration of buoyant and non-buoyant particles in a nanobubble sample used as a next-generation ultrasound contrast agent.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.127
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0030.000

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 head0.040
GPT teacher head0.277
Teacher spread0.237 · 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