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Record W2112023719 · doi:10.1111/mec.13389

Fifty years of co‐evolution and beyond: integrating co‐evolution from molecules to species

2015· article· en· W2112023719 on OpenAlexafffund
Diego Carmona, Connor R. Fitzpatrick, Marc T. J. Johnson

Bibliographic record

VenueMolecular Ecology · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaConsejo Nacional de Ciencia y Tecnología
KeywordsBiologyEvolutionary biologyBiological evolutionMolecular evolutionEcologyPhylogeneticsGeneticsGene

Abstract

fetched live from OpenAlex

Fifty years after Ehrlich and Raven's seminal paper, the idea of co-evolution continues to grow as a key concept in our understanding of organic evolution. This concept has not only provided a compelling synthesis between evolutionary biology and community ecology, but has also inspired research that extends beyond its original scope. In this article, we identify unresolved questions about the co-evolutionary process and advocate for the integration of co-evolutionary research from molecular to interspecific interactions. We address two basic questions: (i) What is co-evolution and how common is it? (ii) What is the unit of co-evolution? Both questions aim to explore the heart of the co-evolutionary process. Despite the claim that co-evolution is ubiquitous, we argue that there is in fact little evidence to support the view that reciprocal natural selection and coadaptation are common in nature. We also challenge the traditional view that co-evolution only occurs between traits of interacting species. Co-evolution has the potential to explain evolutionary processes and patterns that result from intra- and intermolecular biochemical interactions within cells, intergenomic interactions (e.g. nuclear-cytoplasmic) within species, as well as intergenomic interactions mediated by phenotypic traits between species. Research that bridges across these levels of organization will help to advance our understanding of the importance of the co-evolutionary processes in shaping the diversity of life on Earth.

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)0.010
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0030.046
Scholarly communication0.0090.032
Open science0.0020.010
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.216
Teacher spread0.190 · 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 designTheoretical or conceptual
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

Citations48
Published2015
Admission routes2
Has abstractyes

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