MétaCan
Menu
Back to cohort
Record W2034954724 · doi:10.1366/000370207780807803

Background-Free Coherent Anti-Stokes Raman Scattering of Gas- and Liquid-Phase Samples in a Mesoporous Silica Aerogel Host

2007· article· en· W2034954724 on OpenAlexafffund
S. O. Konorov, Robin F. B. Turner, Michael W. Blades

Bibliographic record

VenueApplied Spectroscopy · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSpectroscopy Techniques in Biomedical and Chemical Research
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAerogelNanoporousRaman scatteringMaterials scienceMesoporous silicaScatteringRayleigh scatteringRefractive indexMatrix (chemical analysis)Raman spectroscopyMesoporous materialAnalyteSpectroscopyAnalytical Chemistry (journal)ChemistryOptoelectronicsOpticsNanotechnologyChromatographyComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Efficient time-resolved coherent anti-Stokes Raman scattering (CARS) of atmospheric nitrogen and ethanol trapped in a nanoporous silica aerogel matrix is demonstrated. Silica aerogel hosts are attractive for analytical CARS spectroscopy due to their high porosity/low density, low refractive index, and low scattering cross-section. Differences between the resonant and nonresonant parts of the nonlinear optical susceptibilities lead to much longer relaxation times for analytes compared to the matrix. Time-resolved CARS can then be used to obtain a nearly background-free measurement at characteristic vibrations of the analyte. These results demonstrate the potential of this approach for rapid, sensitive, background-free analyses of analytes entrapped in the aerogel pores, which may be advantageous for some environmental, chemical, and biological sensing applications.

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)0.001
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 score0.005
Threshold uncertainty score0.977

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 studies0.0000.001
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 head0.015
GPT teacher head0.331
Teacher spread0.315 · 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

Citations8
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueApplied SpectroscopySame topicSpectroscopy Techniques in Biomedical and Chemical ResearchFrench-language works237,207