MétaCan
Menu
Back to cohort
Record W2742038423 · doi:10.1002/cbic.201700321

Parallel DNA Synthesis on Poly(ethylene terephthalate)

2017· article· en· W2742038423 on OpenAlexfundno aff
Matthew T. Holden, Matthew C. D. Carter, Shannon K. Ting, David M. Lynn, Lloyd M. Smith

Bibliographic record

VenueChemBioChem · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesNatural Sciences and Engineering Research Council of CanadaNational Institutes of HealthFoundation for the National Institutes of Health
KeywordsOligonucleotideBifunctionalSubstrate (aquarium)Materials scienceEthylenePolymerSurface modificationCombinatorial chemistryCovalent bondNanotechnologyAmine gas treatingDNAChemistryOrganic chemistryBiologyBiochemistryCatalysis

Abstract

fetched live from OpenAlex

The fabrication of DNA arrays directly on aminolyzed sheets of poly(ethylene terephthalate) (PET) is described. Array surfaces typically employ bifunctional linkers or layers of covalently attached polymers to provide substrate hydroxy groups as synthesis attachment points. An amine treatment is used here to expose hydroxy groups on films of PET. These hydroxy groups can then be used to couple phosphoramidites and initiate the array synthesis without further functionalization steps. Arrays fabricated on these substrates with a maskless array synthesizer are tolerant of the high number of chemical exposure steps required to synthesize relatively long oligonucleotides. The results might be of the greatest use to the synthetic biology community, for whom a flexible and robust substrate could enable new strategies to enhance the throughput of oligonucleotide synthesis.

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 score0.021
Threshold uncertainty score0.890

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 head0.016
GPT teacher head0.284
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 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

Citations9
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueChemBioChemSame topicAdvanced biosensing and bioanalysis techniquesFrench-language works237,207