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Record W3094207138 · doi:10.1002/adma.202070316

Multiemission Particle Velocimetry: The Key Role of Intrinsic Lifetime Dynamics from Upconverting Nanosystems in Multiemission Particle Velocimetry (Adv. Mater. 42/2020)

2020· article· en· W3094207138 on OpenAlexaff
Gabriella Tessitore, Steven L. Maurizio, Tarek Sabri, Cameron D. Skinner, John A. Capobianco

Bibliographic record

VenueAdvanced Materials · 2020
Typearticle
Languageen
FieldEngineering
TopicIon-surface interactions and analysis
Canadian institutionsConcordia University
Fundersnot available
KeywordsVelocimetryMaterials scienceParticle tracking velocimetryParticle (ecology)Particle image velocimetryLuminescencePhoton upconversionNanotechnologyOpticsMechanicsOptoelectronicsPhysics

Abstract

fetched live from OpenAlex

In article number 2002266, John A. Capobianco and co-workers present the novel multiemission particle velocimetry technique, which exploits the upconversion luminescence dynamics in core–shell nanoparticles engineered with different emitting ions. Their sequential emissions are characterized by a known time interval, resulting in the possibility of accurately measuring the velocity of the nanoprobes flowing through a microcapillary without the need for any calibration.

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 score0.205
Threshold uncertainty score0.855

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.005
GPT teacher head0.212
Teacher spread0.207 · 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
Published2020
Admission routes1
Has abstractyes

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