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Record W2896423264 · doi:10.1371/journal.pone.0205995

Two novel temperate bacteriophages infecting Streptococcus pyogenes: Their genomes, morphology and stability

2018· article· en· W2896423264 on OpenAlexaff
Marek Harhala, Jakub Barylski, Kinga Humińska‐Lisowska, Dorota Lecion, Jacek Wojciechowicz, Karolina Lahutta, Marta Kuś, Andrew M. Kropinski, Sylwia Nowak, Grzegorz Nowicki, Katarzyna Hodyra‐Stefaniak, Krystyna Dąbrowska

Bibliographic record

VenuePLoS ONE · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversity of Guelph
FundersNarodowe Centrum Nauki
KeywordsSiphoviridaeGenBankBiologyStreptococcus pyogenesGenomeMicrobiologyStreptococcusGeneticsBacteriophageBacteriaGene

Abstract

fetched live from OpenAlex

Only 3% of phage genomes in NCBI nucleotide database represent phages that are active against Streptococcus sp. With the aim to increase general awareness of phage diversity, we isolated two bacteriophages, Str01 and Str03, active against health-threatening Group A Streptococcus (GAS). Both phages are members of the Siphoviridae, but their analysis revealed that Str01 and Str03 do not belong to any known genus. We identified their structural proteins based on LC-ESI29 MS/MS and list their basic thermal stability and physico-chemical features including optimum pH. Annotated genomic sequences of the phages are deposited in GenBank (NCBI accession numbers KY349816 and KY363359, respectively).

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.040
GPT teacher head0.241
Teacher spread0.201 · 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 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

Citations16
Published2018
Admission routes1
Has abstractyes

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