MétaCan
Menu
Back to cohort
Record W3176674743 · doi:10.3389/fevo.2021.636402

Lagomorpha as a Model Morphological System

2021· article· en· W3176674743 on OpenAlexaff
Brian Kraatz, Rafik Belabbas, Łucja Fostowicz‐Frelik, Deyan Ge, Alexander N. Kuznetsov, Madlen M. Lang, Sergi López‐Torres, Zeinolabedin Mohammadi, Rachel A. Racicot, Matthew J. Ravosa, Alana C. Sharp, Emma Sherratt, Mary Silcox, Justyna Słowiak, Alisa J. Winkler, Irina Ruf

Bibliographic record

VenueFrontiers in Ecology and Evolution · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersAlexander von Humboldt-StiftungNational Science Foundation
KeywordsCladeBiologyEvolutionary biologyZoologyMorphology (biology)Diversity (politics)EcologyPhylogeneticsAnthropologyGene

Abstract

fetched live from OpenAlex

Due to their global distribution, invasive history, and unique characteristics, European rabbits are recognizable almost anywhere on our planet. Although they are members of a much larger group of living and extinct mammals [Mammalia, Lagomorpha (rabbits, hares, and pikas)], the group is often characterized by several well-known genera (e.g., Oryctolagus , Sylvilagus , Lepus , and Ochotona ). This representation does not capture the extraordinary diversity of behavior and form found throughout the order. Model organisms are commonly used as exemplars for biological research, but there are a limited number of model clades or lineages that have been used to study evolutionary morphology in a more explicitly comparative way. We present this review paper to show that lagomorphs are a strong system in which to study macro- and micro-scale patterns of morphological change within a clade that offers underappreciated levels of diversity. To this end, we offer a summary of the status of relevant aspects of lagomorph biology.

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 score0.138
Threshold uncertainty score0.683

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 head0.011
GPT teacher head0.204
Teacher spread0.193 · 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

Citations30
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in Ecology and EvolutionSame topicEvolution and Paleontology StudiesFrench-language works237,207