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Record W4385957970 · doi:10.1039/d3ay00842h

A spectIR-fluidic reactor for monitoring fast chemical reaction kinetics with on-chip attenuated total reflection Fourier transform infrared spectroscopy

2023· article· en· W4385957970 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnalytical Methods · 2023
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsCentre hospitalier de l'Université LavalUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAttenuated total reflectionFourier transform infrared spectroscopyInfraredReflection (computer programming)Fourier transformFourier transform spectroscopyInfrared spectroscopyKineticsSpectroscopyAnalytical Chemistry (journal)ChemistryMaterials scienceOpticsChromatographyOrganic chemistryPhysicsComputer science

Abstract

fetched live from OpenAlex

kinetic studies of fast reactions. By integrating a multi-ridge silicon attenuated total reflection (ATR) wafer into the microfluidic device, we enable multi-point measurements for precise reaction time monitoring. As such, this work establishes a validated foundation for studying fast chemical reactions using on-chip ATR-FTIR spectroscopy in a microfluidic reactor environment, which enables simultaneous monitoring of reagents, intermediates, and products using a phosphate proton transfer reaction. The spectIR-fluidic reactor platform offers customizable designs, allowing for the investigation of reactions with various time scales, and has the potential to significantly advance studies exploring reaction mechanisms and optimization.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.552
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.039
GPT teacher head0.354
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