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DURATION AND CONSISTENCY OF HISTORICAL SELECTION ARE CORRELATED WITH ADAPTIVE TRAIT EVOLUTION IN THE STREAMSIDE SALAMANDER,<i>AMBYSTOMA BARBOURI</i>

2009· article· en· W2146964542 on OpenAlexaff
Jonathan M. Eastman, John Niedzwiecki, B. Paul Nadler, Andrew Storfer

Bibliographic record

VenueEvolution · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsASTER
Fundersnot available
KeywordsBiologySalamanderEcologyPredationSalamandridaeSelection (genetic algorithm)Adaptation (eye)TraitLineage (genetic)PredatorPhylogenetic treeEvolutionary biologyCaudataGene

Abstract

fetched live from OpenAlex

A fundamental challenge in evolutionary biology concerns estimating the extent to which ecological trade-offs may impose constraints on adaptive evolution. Novel ecological stressors may limit adaptive evolution of naive lineages that have experienced historically different selective regimes. Regarded as recently derived from a pond-breeding ancestor, streamside salamanders face the novel and strong selection pressure of breeding in streams with fish predators. A statistical phylogenetic approach was used to test whether adaptive evolution of antipredator performance phenotypes in streamside salamanders was positively associated with: (1) estimated per-lineage duration of coexistence with predatory fish; and (2) consistency of this predator selective-regime within lineages. Average durations of fish contact were computed for each salamander lineage on a set of chronograms. Selection consistency was determined by estimating the number of ecological transitions between fish and fishless states using stochastic character mapping. Historical selection in streamside salamanders can be generally characterized as unstable, apparently punctuated by the stochastic loss and recolonization of predatory fish in most lineages. We found that the efficacy of antipredator phenotypes in salamanders is strongly related to historical duration, as well as consistency, of selection imposed by predatory fish.

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 score0.313
Threshold uncertainty score0.300

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 head0.007
GPT teacher head0.190
Teacher spread0.184 · 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

Citations14
Published2009
Admission routes1
Has abstractyes

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