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Record W2046497156 · doi:10.5504/bbeq.2013.0052

Termination Codons and Stop Codon Context in Bacteria and Mammalian Mitochondria

2013· article· en· W2046497156 on OpenAlex
Kiril T. Kirilov, Ashkan Golshani, Iván Ivanov

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.

Bibliographic record

VenueBiotechnology & Biotechnological Equipment · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsCarleton University
Fundersnot available
KeywordsStop codonBiologyGeneMitochondrionStart codonGeneticsGenomeContext (archaeology)Mitochondrial DNACodon usage biasTranslation (biology)Open reading frameNucleotideMessenger RNAPeptide sequence

Abstract

fetched live from OpenAlex

The aim of this study was to analyze the frequency of occurrence of individual stop codons and combinations of stop codons with adjacent upstream and downstream triplets in 264 bacterial and 1308 mammalian mitochondrial genomes. For the purpose of this analysis a novel program (Gene Triplet Analysis) was applied. The obtained results indicate that the standard stop codon UAA is the most frequently used one (48%) in both bacteria and mitochondria. In addition, our analysis revealed 30 nonstandard translation termination codons in mitochondria. The preferential nucleotides in all three positions adjacent to the stop codons in mammalian mitochondria are A and U.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
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 score0.163
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0020.000
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 head0.010
GPT teacher head0.221
Teacher spread0.211 · 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