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Record W2805532333 · doi:10.1086/698170

The Role of Phenotypic Plasticity in Moderating Evolutionary Conflict

2018· article· en· W2805532333 on OpenAlexafffund
Troy Day, David V. McLeod

Bibliographic record

VenueThe American Naturalist · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCoevolutionSexual conflictEvolutionary dynamicsEvolutionary biologyPhenotypic plasticityBiologyMechanism (biology)Adaptation (eye)EcologySexual selectionSociologyEpistemologyNeurosciencePopulation

Abstract

fetched live from OpenAlex

Evolutionary conflicts arise when the fitness interests of interacting individuals differ. Well-known examples include sexual conflict between males and females and antagonistic coevolution between hosts and parasites. A common feature of such conflicts is that compensating evolutionary change in each of the parties can lead to little overt change in the interaction itself. As a result, evolutionary conflict is expected to persist even if the evolutionary dynamic between the parties reaches an equilibrium. In these cases, it is of interest to know whether certain kinds of interactions are expected to lead to greater or lesser evolutionary conflict at such evolutionary stalemates. Here we present a theoretical analysis showing that when one of the interacting parties can respond to the other through adaptive phenotypic plasticity, evolutionary conflict is reduced. Paradoxically, however, it is the party that does not express adaptive plasticity that experiences less conflict. Conflict for the party displaying adaptive plasticity can increase or decrease, depending on the situation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.875
Threshold uncertainty score0.475

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 studies0.0000.001
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 head0.022
GPT teacher head0.225
Teacher spread0.203 · 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

Citations10
Published2018
Admission routes2
Has abstractyes

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