MétaCan
Menu
Back to cohort
Record W3023853601 · doi:10.1016/j.tree.2020.04.003

Disease-mediated ecosystem services: Pathogens, plants, and people

2020· article· en· W3023853601 on OpenAlexaff
Rachel E. Paseka, Lauren A. White, Dedmer B. Van de Waal, Alexander T. Strauss, Angélica L. González, Rebecca A. Everett, Angela Peace, Eric W. Seabloom, Thijs Frenken, Elizabeth T. Borer

Bibliographic record

VenueTrends in Ecology & Evolution · 2020
Typearticle
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsUniversity of Windsor
FundersNational Socio-Environmental Synthesis CenterNational Science Foundation
KeywordsEcosystem servicesProvisioningEcosystemEnvironmental resource managementAutotrophEcosystem healthBusinessEcologyBiologyEnvironmental planningGeographyEnvironmental scienceComputer science

Abstract

fetched live from OpenAlex

Despite the ubiquity of pathogens in ecological systems, their roles in influencing ecosystem services are often overlooked. Pathogens that infect primary producers (i.e., plants, algae, cyanobacteria) can have particularly strong effects because autotrophs are responsible for a wide range of provisioning, regulating, and cultural services. We review the roles of pathogens in mediating ecosystem services provided by autotrophs and outline scenarios in which infection may lead to unexpected outcomes in response to global change. Our synthesis highlights a deficit of information on this topic, and we outline a vision for future research that includes integrative theory and cross-system empirical studies. Ultimately, knowledge about the mediating roles of pathogens on ecosystem services should inform environmental policy and 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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.498

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)0.0000.000

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 head0.014
GPT teacher head0.258
Teacher spread0.244 · 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 designObservational
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

Citations69
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueTrends in Ecology & EvolutionSame topicZoonotic diseases and public healthFrench-language works237,207