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Record W2165400731 · doi:10.1002/anie.201001604

Synchronized Synthesis of Peptide‐Based Macrocycles by Digital Microfluidics

2010· article· en· W2165400731 on OpenAlexafffund
Mais J. Jebrail, Alphonsus H. C. Ng, Vishal Rai, Ryan Hili, Andrei K. Yudin, Aaron R. Wheeler

Bibliographic record

VenueAngewandte Chemie International Edition · 2010
Typearticle
Languageen
FieldEngineering
TopicElectrowetting and Microfluidic Technologies
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsAziridinePeptideMicrofluidicsReagentCombinatorial chemistryNanotechnologyChemistryDigital microfluidicsElectrodeSide chainRing (chemistry)Materials scienceOrganic chemistryPolymerBiochemistry

Abstract

fetched live from OpenAlex

Digital synthesis has been applied to the formation of peptide-based macrocycles and their analogues with side chains appended during late-stage aziridine ring-opening. Discrete nanoliter- to microliter-sized droplets of samples and reagents are controlled in parallel by applying a series of electrical potentials to an array of electrodes coated with a hydrophobic insulator.

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 score0.001
Threshold uncertainty score0.002

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.199
Teacher spread0.195 · 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

Citations107
Published2010
Admission routes2
Has abstractyes

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