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Record W7140764645 · doi:10.1333/s00897112399a

Microscale Catalytic and Chemoselective TPAP Oxidation of Geraniol

2011· article· en· W7140764645 on OpenAlexaff
Katherine J. Koroluk, Stanislaw Skonieczny, Andrew P. Dicks

Bibliographic record

VenueThe Chemical Educator · 2011
Typearticle
Languageen
FieldChemistry
TopicVarious Chemistry Research Topics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGeraniolCatalysisAutocatalysisAlcoholMicroscale chemistrySubstrate (aquarium)Reactivity (psychology)Alcohol oxidation

Abstract

fetched live from OpenAlex

The mild, room-temperature oxidation of a primary alcohol catalyzed by tetrapropylammonium perruthenate (TPAP) is presented for the undergraduate organic laboratory. In this experiment, geraniol is oxidized to form geranial, a liquid product that is easily characterized via IR and proton NMR spectroscopy. Both substrate and product have very distinct and pleasant odours, so their respective reactivity and formation generates class interest. Comparison between this synthesis and other alcohol oxidation procedures affords discussion of catalytic behaviour apparent in the former method. Although catalysis is favourable in terms of green chemistry, certain improvements can be made from a sustainability perspective, which is an important focal point for student discourse. The reaction also provides an opportunity to perform a reaction under dry conditions, and to investigate a detailed autocatalytic mechanism of TPAP oxidation.

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 score0.001
Threshold uncertainty score0.004

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.025
GPT teacher head0.248
Teacher spread0.223 · 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

Citations2
Published2011
Admission routes1
Has abstractyes

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