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Record W2783924519 · doi:10.1055/s-0036-1589159

Synthesis of Heterobenzylic Fluorides

2018· article· en· W2783924519 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSynthesis · 2018
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicFluorine in Organic Chemistry
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsChemistryElectrophileHalideFluorideElectrophilic fluorinationHalogenationLipophilicityElectrophilic substitutionMoleculeMedicinal chemistryElectrophilic additionOrganic chemistryInorganic chemistryCatalysis

Abstract

fetched live from OpenAlex

Fluorination at heterobenzylic positions can have a significant impact on basicity, lipophilicity, and metabolism of drug leads. As a consequence, the development of new methods to access heterobenzylic fluorides has particular relevance to medicinal chemistry. This short review provides a survey of common methods used to synthesize heterobenzylic fluorides and includes fluoride displacement reactions of previously functionalized molecules (e.g., deoxyfluorination and halide exchange) and electrophilic fluorination of resonance-stabilized heterobenzylic anions. In addition, recent advances in the direct fluorination of heterobenzylic C(sp3)–H bonds and monofluoromethylation of heterocyclic C(sp2)–H bonds are presented. 1 Introduction 2 Heterobenzylic Fluorides 2.1 Deoxyfluorination 2.2 Halide Exchange 2.3 Electrophilic Fluorination of Heterobenzylic Anions 2.4 Late Stage C–H Bond Fluorination 2.5 Monofluoromethylation of C(sp2)–H Bonds 3 Conclusions

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.074
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.001

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 head0.075
GPT teacher head0.398
Teacher spread0.323 · 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