MétaCan
Menu
Back to cohort
Record W1970252762 · doi:10.1186/1475-2859-13-s1-s1

Progress in lactic acid bacterial phage research

2014· review· en· W1970252762 on OpenAlexfundno aff
Jennifer Mahony, Francesca Bottacini, Douwe van Sinderen, Gerald F. Fitzgerald

Bibliographic record

VenueMicrobial Cell Factories · 2014
Typereview
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsnot available
FundersScience Foundation IrelandUniversité Laval
KeywordsBacteriophageLactic acidHost (biology)Computational biologySynthetic biologyBiologyPhage therapyComputer scienceData scienceBacteriaGenetics

Abstract

fetched live from OpenAlex

Research on lactic acid bacteria (LAB) has advanced significantly over the past number of decades and these developments have been driven by the parallel advances in technologies such as genomics, bioinformatics, protein expression systems and structural biology, combined with the ever increasing commercial relevance of this group of microorganisms. Some of the more significant and impressive outputs have been in the domain of bacteriophage-host interactions which provides a prime example of the cutting-edge model systems represented by LAB research. Here, we present a retrospective overview of the key advances in LAB phage research including phage-host interactions and co-evolution. We describe how in many instances this knowledge can be pivotal in creating real improvements in the application of LAB cultures in commercial practice.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.053
GPT teacher head0.360
Teacher spread0.307 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations52
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueMicrobial Cell FactoriesSame topicBacteriophages and microbial interactionsFrench-language works237,207