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Record W4281766717 · doi:10.26434/chemrxiv-2022-j87g9

Total Synthesis of Matrine Alkaloids

2022· preprint· en· W4281766717 on OpenAlexfundno aff
Nicholas L. Magann, Erin Westley, Madison J. Sowden, Michael G. Gardiner, Michael S. Sherburn

Bibliographic record

VenueChemRxiv · 2022
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioactive natural compounds
Canadian institutionsnot available
FundersAustralian Research CouncilUniversité de Sherbrooke
KeywordsMatrineNatural productTotal synthesisChemistryIntramolecular forceDiastereomerStereochemistryCovalent bondCombinatorial chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The total synthesis of three diastereomeric matrine natural products is reported. The eight-step synthesis commences with simple acyclic precursors, forms all four rings of the tetracyclic natural product framework and forges ten of the twenty covalent bonds of the target structure. The chemical synthesis adopts an unprecedented strategy that encompasses both transform and stereochemical attributes. A cross-conjugated triene is positioned at the core of an acyclic branched structure, which collapses to the tetracyclic natural product framework through an orchestrated sequence of two intramolecular cycloadditions. A subsequent, late-stage hydrogenation is accompanied by strain-release redox epimerizations to deliver the three natural products. Semisynthetic manipulations of matrine provide access to ten additional natural products.

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 score0.005
Threshold uncertainty score0.015

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 science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.011
GPT teacher head0.255
Teacher spread0.244 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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