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Record W4377565482 · doi:10.1002/cpz1.784

Synthesis of Dinucleotide Non‐Symmetrical Triester Phosphate Phosphoramidites and Their Incorporation Within Oligonucleotides

2023· article· en· W4377565482 on OpenAlexaff
Jean‐Paul Desaulniers, Kouta Tsubaki, Matthew L. Hammill, Mitsuru Kitamura, Tatsuo Okauchi

Bibliographic record

VenueCurrent Protocols · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsPhosphoramiditeChemistryPhosphateOligonucleotideNucleotideCombinatorial chemistryOligonucleotide synthesisTrisOrganic chemistryBiochemistryDNA

Abstract

fetched live from OpenAlex

In this protocol article, the synthesis of dinucleotide non-symmetrical triester phosphate phosphoramidites will be highlighted. Specifically, we use a selective transesterification starting with tris(2,2,2-trifluoroethyl) phosphate to afford a dinucleotide derivative phosphate ester. Substitution of the final trifluoroethyl group with various alcohols affords a dinucleotide triester phosphate with a hydrophobic group, which can then be deprotected and converted to a phosphoramidite for incorporation within oligonucleotides. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Synthesis of a DMT- and TBS-protected unsymmetrical dinucleotide Basic Protocol 2: Synthesis of a DMT-protected unsymmetrical dinucleotide phosphotriester monoalcohols Basic Protocol 3: Synthesis of DMT-protected phenylethyl phosphotriester dinucleotide phosphoramidites Basic Protocol 4: Synthesis, purification, and characterization of RNAs containing triester phosphate modifications.

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: Methods · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0040.002

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 head0.022
GPT teacher head0.290
Teacher spread0.268 · 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
GenreMethods

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
Published2023
Admission routes1
Has abstractyes

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