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Record W2767173754 · doi:10.1101/203687

Virulence evolution of a parasite infecting male and female hosts

2017· preprint· en· W2767173754 on OpenAlexaff
Alison M. Wardlaw, Aneil F. Agrawal

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2017
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiologyVirulencePathogenHost (biology)Transmission (telecommunications)Parasite hostingTraitPopulationSusceptible individualTransmission rateZoologyEcologyGeneticsDemographyGene

Abstract

fetched live from OpenAlex

Abstract Parasites experience different tradeoffs between transmission and virulence in male and female hosts if the sexes vary in life history or disease-related traits. We determine the evolutionarily stable levels of exploitation by pathogens under two scenarios: an unconstrained pathogen that expresses different exploitation rates within each host type as well as a pathogen constrained to express the same exploitation rate in each sex. We show that an unconstrained horizontally-transmitted parasite evolves to express the same sex-specific exploitation rate within each sex as it would in a host population composed entirely of hosts with that sex’s resistance and intrinsic death rate. In contrast, the ESS exploitation rate of a constrained pathogen is affected by sex-differences in susceptibility and non-random contact patterns between host types that differ in resistance. As the amount of within-sex transmission increases, the ESS shifts closer to the optimum trait value in the more susceptible sex. Allowing for some degree of vertical transmission, the exploitation rate expressed in females (but not males) changes with contact pattern even in unconstrained pathogens. Differences in contact pattern and susceptibility play an important role in determining the ESS exploitation rate by shifting the reproductive value of each host type.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.009
GPT teacher head0.237
Teacher spread0.228 · 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 designSimulation or modeling
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

Citations0
Published2017
Admission routes1
Has abstractyes

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