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Record W2977415541 · doi:10.1039/c9na00487d

A multiwavelength emission detector for analytical ultracentrifugation

2019· article· en· W2977415541 on OpenAlex
Simon E. Wawra, G. Onishchukov, Maria Maranska, Siegfried Eigler, Johannes Walter, Wolfgang Peukert

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 Advances · 2019
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsInstitute of Particle Physics
FundersDeutsche Forschungsgemeinschaft
KeywordsAnalytical UltracentrifugationFluorescenceQuantum dotAnalytical Chemistry (journal)Materials scienceParticle sizeSpectrometerParticle (ecology)UltracentrifugeDetectorEmission spectrumPhotoluminescenceSpectral lineNanotechnologyChemistryChromatographyOpticsOptoelectronicsPhysicsPhysical chemistry

Abstract

fetched live from OpenAlex

comparison to a benchtop photoluminescence spectrometer and the established extinction-based multiwavelength analytical ultracentrifuge (MWL-AUC). The results on fluorescent proteins and silica particles demonstrate that the new device not only correctly reproduces sedimentation and diffusion coefficients of the particles but provides also meaningful fluorescence spectra. As an application example for a sample exhibiting a broad particle size distribution, spectra and size of graphene oxide nanoplatelets are extracted simultaneously. Narrowly distributed CdSe/ZnS quantum dots showing size- and structure-dependent shifts of their fluorescence spectra are analyzed as well. The combination of MWE- and MWL-AUC provides a comprehensive framework for the optical characterization for nanoparticles and macromolecules in terms of their extinction and emission properties.

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)0.000
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 score0.051
Threshold uncertainty score0.303

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 head0.010
GPT teacher head0.262
Teacher spread0.252 · 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