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Record W2765649691 · doi:10.1002/9781119092599.ch1

Contemporary Macrocyclization Technologies

2017· other· en· W2765649691 on OpenAlexaff
Serge Zaretsky, Andrei K. Yudin

Bibliographic record

Venuenot available
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChemical Synthesis and Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCombinatorial chemistryChemistryHeteroatomChemical spaceNanotechnologyRing (chemistry)Organic moleculesMoleculeOrganic chemistryDrug discoveryMaterials science

Abstract

fetched live from OpenAlex

In medicinal chemistry, macrocycles occupy the “middle space” between small organic molecules and proteins. Macrocycles can be based on primarily aliphatic backbones as exemplified by macrolides or on heteroatom-based scaffolds as exemplified by macrocyclic polyethers. The benefits of macrocycles are vast, especially when compared with their linear analogues, but there are some challenges inherent to their synthesis and isolation. In the realm of macrocycle characterization, routine techniques are often used at their limit or they can be even completely ineffective. For example, the simple TLC experiment, a standard technique of organic chemistry, can be wholly ineffective for many classes of macrocycles. This chapter focuses on macrocyclization methods and cyclization on the solid phase. Development of new macrocyclization methods continues to be an active area of research. Method development can be for the most part separated between the search for novel ring-closing reactions and improvements of established methods.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.070
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.251
Teacher spread0.239 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations4
Published2017
Admission routes1
Has abstractyes

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