MétaCan
Menu
Back to cohort
Record W2099827637 · doi:10.1186/1754-1611-8-28

The case for decoupling assembly and submission standards to maintain a more flexible registry of biological parts

2014· article· en· W2099827637 on OpenAlexfundno aff
Razan N. Alnahhas, Ben Slater, Yunle Huang, Catherine Mortensen, Jordan W. Monk, Yousef Okasheh, Marco D. Howard, Neil Gottel, Michael J. Hammerling, Jeffrey E. Barrick

Bibliographic record

VenueJournal of Biological Engineering · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsnot available
FundersUniversity of Texas at AustinUniversity of OttawaNorth Carolina Agricultural and Technical State UniversityNational Science Foundation
KeywordsComputer scienceDecoupling (probability)Sequence (biology)Computational biologyBiologyGeneticsEngineeringControl engineering

Abstract

fetched live from OpenAlex

The Registry of Standard Biological Parts only accepts genetic parts compatible with the RFC 10 BioBrick format. This combined assembly and submission standard requires that four unique restriction enzyme sites must not occur in the DNA sequence encoding a part. We present evidence that this requirement places a nontrivial burden on iGEM teams developing large and novel parts. We further argue that the emergence of inexpensive DNA synthesis and versatile assembly methods reduces the utility of coupling submission and assembly standards and propose a submission standard that is compatible with current quality control strategies while nearly eliminating sequence constraints on submitted parts.

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)0.132
metaresearch head score (Gemma)0.096
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.132
Threshold uncertainty score0.696

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1320.096
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.004
Science and technology studies0.0040.008
Scholarly communication0.0140.029
Open science0.0080.011
Research integrity0.0080.019
Insufficient payload (model declined to judge)0.0050.006

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 head0.015
GPT teacher head0.323
Teacher spread0.308 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations7
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Biological EngineeringSame topicCRISPR and Genetic EngineeringFrench-language works237,207