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Record W2036536037 · doi:10.1002/adsc.200800516

β‐Hydroxycarboxylic Acids from Simple Ketones by Carboxylation and Asymmetric Hydrogenation

2008· article· en· W2036536037 on OpenAlexaff
Brendan J. Flowers, Robyn Gautreau‐Service, Philip G. Jessop

Bibliographic record

VenueAdvanced Synthesis & Catalysis · 2008
Typearticle
Languageen
FieldChemistry
TopicAsymmetric Hydrogenation and Catalysis
Canadian institutionsQueen's University
Fundersnot available
KeywordsCarboxylationChemistryAsymmetric hydrogenationSubstrate (aquarium)SolventEnolYield (engineering)Organic chemistryCatalysisNoyori asymmetric hydrogenationEnantioselective synthesis

Abstract

fetched live from OpenAlex

Abstract We present a new asymmetric synthesis of β‐hydroxycarboxylic acids from ketones, performed by carboxylation using CO2 followed by asymmetric hydrogenation. First, the carboxylation of ketones gives β‐ketocarboxylic acids. The effects of temperature, reaction time, and amount of 1,8‐diazabicyclo[5.4.0]undec‐7‐ene (DBU) promoter on the carboxylation were investigated. The DBU can be recycled. For the second step, the asymmetric hydrogenation of these β‐ketocarboxylic acids, we determined the effect of solvent choice, H2 pressure, and substrate substitution. Hydrogenation yield and enantioselectivity are solvent‐dependent, and the mechanism could proceed through hydrogenation of either the enol or the keto forms of the bound substrate. This synthesis is industrially advantageous due to the limited number of reactants required, their low‐cost, and the potential for recycling unused materials.

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.213
Teacher spread0.205 · 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

Citations61
Published2008
Admission routes1
Has abstractyes

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