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Record W7132973652

A new guanidinylation procedure for the preparation of functionalized guanidines and investigation towards the synthesis of cyclic quanidine compounds

2003· dissertation· W7132973652 on OpenAlexaboutno aff
Philip Dean Ramsden

Bibliographic record

VenueTSpace · 2003
Typedissertation
Language
FieldChemistry
TopicSynthesis of heterocyclic compounds
Canadian institutionsnot available
Fundersnot available
KeywordsGuanidineAlkylationHalideAlkylPalladium
DOInot available

Abstract

fetched live from OpenAlex

This thesis is a summary of research conducted since October 2000 at the University of Toronto in the laboratory of Dr. Robert A. Batey. This manuscript is divided into three chapters. Chapter one provides a brief introduction to the guanidine functional group and guanidine-containing compounds, both natural and synthetic. Chapter two describes a new method for alkylation of guanidine-containing compounds using a convenient and mild biphasic protocol. This approach requires limited purification of the obtained products, yielding highly functionalized guanidines in good to excellent yields. This protocol has been used with a variety of alkyl halides and mesylates and provides an alternate approach to methods currently utilized in the literature. Chapter three describes investigations towards the synthesis of cyclic guanidine compounds. Initially, iodocyclization reactions were attempted; however, limited success was encountered with this approach. Palladium-catalyzed π-allyl chemistry was then investigated to synthesize the cyclic guanidine compounds. Thus far, investigations with this approach have been successful and a general approach for the synthesis of cyclic guanidine compounds using palladium π-allyl chemistry is described for the first time within our labs.

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 score0.003
Threshold uncertainty score0.012

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.039
GPT teacher head0.327
Teacher spread0.289 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

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