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Record W2070354327 · doi:10.1039/c2np20108a

α-Haloaldehydes: versatile building blocks for natural product synthesis

2012· review· en· W2070354327 on OpenAlexaff
Robert Britton, Baldip Kang

Bibliographic record

VenueNatural Product Reports · 2012
Typereview
Languageen
FieldChemistry
TopicAsymmetric Synthesis and Catalysis
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsNatural productEnantioselective synthesisReagentCombinatorial chemistryStereoselectivityNatural (archaeology)Organic synthesisChemistryBiochemical engineeringComputer scienceOrganic chemistryCatalysisBiologyEngineering

Abstract

fetched live from OpenAlex

The diastereoselective addition of organometallic reagents to α-chloroaldehydes was first reported in 1959 and occupies a historically significant role as the prototypical reaction for Cornforth's model of stereoinduction. Despite clear synthetic potential for these reagents, difficulties associated with producing enantiomerically enriched α-haloaldehydes limited their use in natural product synthesis through the latter half of the 20th century. In recent years, however, a variety of robust, organocatalytic processes have been reported that now provide direct access to optically enriched α-haloaldehydes and have motivated renewed interest in their use as building blocks for natural product synthesis. This Highlight summarizes the methods available for the enantioselective preparation of α-haloaldehydes and their stereoselective conversion into natural products.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.004

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 head0.033
GPT teacher head0.303
Teacher spread0.270 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations57
Published2012
Admission routes1
Has abstractyes

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