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Record W4307430932 · doi:10.1002/jez.2666

Evolution in reproductive tempo and investment across the <i>Peromyscus</i> radiation

2022· review· en· W4307430932 on OpenAlexfundno aff
Kathryn Wilsterman, Kirksey Cunningham

Bibliographic record

VenueJournal of Experimental Zoology Part A Ecological and Integrative Physiology · 2022
Typereview
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human DevelopmentUniversity of California, DavisMcMaster UniversityNational Science FoundationNational Institutes of HealthUniversity of MontanaHarvard University
KeywordsPeromyscusBiologyEcologyPhenologyAdaptation (eye)ZoologyLitterEvolutionary biology

Abstract

fetched live from OpenAlex

Mammals display diverse reproductive strategies, however, the ultimate and proximate mechanisms that underlie this diversity and its composite traits remain poorly understood from both evolutionary and physiological perspectives. The Peromyscus genus of rodents, which is found throughout the north and central Americas, has diversified along life history gradients, varying both within and among species in reproductive strategies. This variation provides a useful model for studying reproductive diversity. Here, we combine a literature review with new analyses of captive colony breeding records from six Peromyscus species to assess our current understanding of how plasticity and local adaptation contribute to diversity in two classes of reproductive traits: phenology and litter investment. There is substantial evidence that many traits underlying phenology and litter investment have diverged among populations in ways that are likely to be locally adaptive, though plasticity in these traits remains common. However, these conclusions are largely based on data collected from the two most widespread Peromyscus species: P. maniculatus and P. leucopus. The majority of Peromyscus species diversity remains understudied regarding reproductive phenology and litter traits. We conclude by discussing key challenges and considerations relevant to using Peromyscus as a mammalian model for reproductive trait diversity and evolution moving forward.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.788
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.338
Teacher spread0.294 · 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.

Study designNot applicable
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

Citations8
Published2022
Admission routes1
Has abstractyes

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