MétaCan
Menu
Back to cohort
Record W2002981040 · doi:10.1371/journal.ppat.0020042

Crossing the Line: Selection and Evolution of Virulence Traits

2006· review· en· W2002981040 on OpenAlexafffund
Nat F. Brown, Mark E. Wickham, Brian K. Coombes, B. Brett Finlay

Bibliographic record

VenuePLoS Pathogens · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsCanada's Michael Smith Genome Sciences CentreHealth Sciences CentreMcMaster University Medical CentreUniversity of British Columbia
FundersCanadian Institutes of Health ResearchKillam TrustsMichael Smith Health Research BCHoward Hughes Medical Institute
KeywordsVirulenceBiologySelection (genetic algorithm)Natural selectionHuman evolutionary geneticsEvolutionary biologyHost (biology)PhenotypeGeneticsExperimental evolutionEvolutionary dynamicsPhylogeneticsGenePopulationComputer science

Abstract

fetched live from OpenAlex

The evolution of pathogens presents a paradox. Pathogenic species are often absolutely dependent on their host species for their propagation through evolutionary time, yet the pathogenic lifestyle requires that the host be damaged during this dependence. It is clear that pathogenic strategies are successful in evolutionary terms because a diverse array of pathogens exists in nature. Pathogens also evolve using a broad range of molecular mechanisms to acquire and modulate existing virulence traits in order to achieve this success. Detailing the benefit of enhanced selection derived through virulence and understanding the mechanisms through which virulence evolves are important to understanding the natural world and both have implications for human health.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.020
GPT teacher head0.284
Teacher spread0.264 · 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

Citations101
Published2006
Admission routes2
Has abstractyes

Explore more

Same venuePLoS PathogensSame topicEvolution and Genetic DynamicsFrench-language works237,207