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Record W2114831642 · doi:10.1071/ch14386

A Simple and Efficient Two-Step Synthesis of 1,2,3-Triiodoarenes via Consecutive C–H Iodination/ipso-Iododecarboxylation Strategy: A Potential Application towards ortho-Diiodoarenes by Regioselective Metal–Iodine Exchange Reaction

2014· article· en· W2114831642 on OpenAlexafffund
Raed M. Al‐Zoubi, Hussein Al‐Mughaid, Robert McDonald

Bibliographic record

VenueAustralian Journal of Chemistry · 2014
Typearticle
Languageen
FieldChemistry
TopicCatalytic C–H Functionalization Methods
Canadian institutionsAlberta Glycomics CentreUniversity of Alberta
FundersUniversity of JordanApplied Scientific Research FundJordan University of Science and TechnologyUniversity of Alberta
KeywordsRegioselectivityChemistryCombinatorial chemistryBiocatalysisIodineGreen chemistryHalogenationOrganic chemistryReaction mechanismCatalysis

Abstract

fetched live from OpenAlex

A general, robust, and efficient method for the conversion of benzoic acids to 1,2,3-triiodoarenes and 1,2,3-trihaloarenes via a two-step synthesis is reported. Commercially available benzoic acids were used that can allow the reactions to be performed on multi-gram scales with good-to-excellent yields. This report discloses a practical method for the synthesis of 1,2,3-triiodoarenes and 1,2,3-trihaloarenes that is general in scope, scalable, and easy to workup and purify. A potential application of the target compounds as precursors for novel regioselective metal–iodine exchange reaction of 1,2,3-triiodoarenes was also demonstrated. It provided ortho-diiodoaryl derivatives in a high regioselective fashion that are useful intermediates in synthesis and indeed are hard to synthesize by any other means.

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.280
Teacher spread0.263 · 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

Citations16
Published2014
Admission routes2
Has abstractyes

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