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Record W2013727620 · doi:10.2144/000113369

Improving Sequencing Quality from PCR Products Containing Long Mononucleotide Repeats

2010· article· en· W2013727620 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBioTechniques · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsUniversity of Guelph
FundersUniversity of GuelphOntario Genomics InstituteGenome Canada
KeywordsProofreadingBiologyGeneticsPolymeraseDNA polymeraseDNAPolymerase chain reactionSequence (biology)NucleotideMicrosatelliteComputational biologyMolecular biologyAlleleGene

Abstract

fetched live from OpenAlex

Stutter products are a common artifact in the PCR amplification of frequently used genetic markers that contain mononucleotide simple sequence repeats. Despite the importance of accurate determination of nucleotide sequence and allele size, there has been little progress toward decreasing the formation of stutter products during PCR. In this study, we tested the effects of lowered extension temperatures, inclusion of co-solutes in PCR, PCR cycle number, and the use of different polymerases on sequence quality for a set of sequences containing mononucleotide A/T repeats of 10-17 bp. Our analyses showed that sequence quality of mononucleotide repeats <or=15 bp is greatly improved with the use of proofreading DNA polymerases fused to nonspecific dsDNA binding domains. Our findings also suggest that the number of nucleotides with which the DNA polymerase interacts may be the most important factor in the reduction of slipped-strand mispairings in vitro.

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.

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)0.001
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 score0.023
Threshold uncertainty score0.932

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0010.000
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 head0.294
Teacher spread0.275 · 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