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Record W4200139682 · doi:10.1089/phage.2021.0013

Phage Annotation Guide: Guidelines for Assembly and High-Quality Annotation

2021· article· en· W4200139682 on OpenAlexaff
Dann Turner, Evelien M. Adriaenssens, Igor Tolstoy, Andrew M. Kropinski

Bibliographic record

VenuePHAGE · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversity of Guelph
FundersBiotechnology and Biological Sciences Research Council
KeywordsAnnotationSequence assemblyGenomeSequence (biology)Genome projectGenomicsComputational biologyDNA sequencingWhole genome sequencingBiologyWorld Wide WebInformation retrievalGeneticsComputer scienceGene

Abstract

fetched live from OpenAlex

All sequencing projects of bacteriophages (phages) should seek to report an accurate and comprehensive annotation of their genomes. This article defines 14 questions for those new to phage genomics that should be addressed before submitting a genome sequence to the International Nucleotide Sequence Database Collaboration or writing a publication.

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 score0.465
Threshold uncertainty score0.994

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)0.0010.000

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 head0.066
GPT teacher head0.386
Teacher spread0.320 · 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

Citations75
Published2021
Admission routes1
Has abstractyes

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