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Record W6892276540 · doi:10.5061/dryad.p33nq17

Data from: Host traits and competitive ability jointly structure disease dynamics and community assembly

2019· dataset· en· W6892276540 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2019
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCompetition (biology)TraitHost (biology)ParasitismParasite hostingCompetitor analysisResource Acquisition Is InitializationInterspecific competition

Abstract

fetched live from OpenAlex

1. Parasitism and competition are both ubiquitous interactions in ecological communities. The ability of host species to interact directly via competition and indirectly through shared parasites suggests that host traits related to competition and parasitism are likely important in structuring communities and disease dynamics. Specifically, those host traits affecting competition and those mediating parasitism are often correlated either because of trade-offs (in resource acquisition or resource allocation) or condition-dependence; yet the consequences of these trait relationships for community and epidemiological dynamics are poorly understood. 2. We conducted a literature review of parasite-related host traits – competitive ability relationships. We found that transmission – competitive ability relationships were most often reported, and that superior competitors exhibited elevated transmission relative to their less-competitive counterparts in nearly 80% of the cases. We also found a significant number of virulence – competitive ability and parasite shedding – competitive ability relationships. 3. We investigated these links by altering the relationship between host competitive ability and three parasite-related traits (transmission, virulence, and parasite shedding rates) in a simple model, incorporating competitive asymmetries in a multi-host community. 4. We show that these relationships can lead to a range of different communities. For example, depending on the strength and direction of these distinct trait relationships, we observed communities with anywhere from high parasite prevalence to complete parasite extinction, and either one, two, or the maximum of three host species coexisting. 5. Our results suggest that parasite – competitive ability relationships may be common in nature, that further integration of these relationships can produce novel and unexpected community and disease dynamics, and that generalizations may allow for the prediction of how parasitism and competition jointly structure disease and diversity in natural communities.

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)0.004
metaresearch head score (Gemma)0.024
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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.250
Threshold uncertainty score0.837

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.2500.094

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 head0.058
GPT teacher head0.282
Teacher spread0.225 · 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
GenreDataset

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

Citations1
Published2019
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)→French-language works237,207→