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Record W4323649788 · doi:10.1039/d2bm02014a

Optimization of precision nanofiber micelleplexes for DNA delivery

2023· article· en· W4323649788 on OpenAlexafffund
Steven T. G. Street, Hayley C. Parkin, Lennard K. Shopperly, Josie Chrenek, Keiran Letwin, Stephanie M. Willerth, Ian Manners

Bibliographic record

VenueBiomaterials Science · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsUniversity of British ColumbiaUniversity of Victoria
FundersBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsEngineering and Physical Sciences Research CouncilCanada Foundation for InnovationUniversity of Victoria
KeywordsNanofiberTransfectionNucleic acidNanotechnologyPolymerGene deliveryChemistryMethacrylateDNABiophysicsMaterials scienceBiochemistryMonomerOrganic chemistryBiology

Abstract

fetched live from OpenAlex

upon transfection efficiency and cell viability. These studies are vital for understanding the formation and biological activity of micelleplexes in more detail and should inform the future design of more advanced polymeric NA delivery systems.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.262

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 head0.020
GPT teacher head0.278
Teacher spread0.259 · 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 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

Citations8
Published2023
Admission routes2
Has abstractyes

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