MétaCan
Menu
Back to cohort
Record W2103065808 · doi:10.1039/c4cy00018h

‘From the mole to the molecule’: ruthenium catalyzed nitroarene reduction studied with ‘bench’, high-throughput and single molecule fluorescence techniques

2014· article· en· W2103065808 on OpenAlexafffund
Adela I. Carrillo, Kevin G. Stamplecoskie, M. Luisa Marín, J. C. Scaiano

Bibliographic record

VenueCatalysis Science & Technology · 2014
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsCatalysisRutheniumFluorescenceMoleculePhotochemistryChemistryAmine gas treatingSpectroscopyFluorescence spectroscopyOrganic chemistry

Abstract

fetched live from OpenAlex

Single molecule fluorescence microscopy techniques are used to complement conventional catalysis and high-throughput experiments in order to gain a complete picture of a model reaction. In these experiments a model nitroarene is reduced to an amine where, upon reduction, a red shift in absorption/emission, as well as an increase in emission, is observed. The reaction is studied under bulk reaction conditions by NMR spectroscopy and the fluorescence activation makes it possible to also study this reaction at the single molecule level. Fluorescence correlation spectroscopy is a valuable technique in supporting the proposed reaction mechanism and understanding the nature and duration of molecular ‘visits’ to catalytic sites, where both the starting material, nitroarene, and the amine product have an affinity for the catalyst.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.004
GPT teacher head0.193
Teacher spread0.189 · 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 source (direct Gemma or distilled Codex), 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

Citations23
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueCatalysis Science & TechnologySame topicMolecular Junctions and NanostructuresFrench-language works237,207