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Record W2634479443 · doi:10.1002/ece3.3120

Evolution of mammalian migrations for refuge, breeding, and food

2017· article· en· W2634479443 on OpenAlexaff
Gitanjali E. Gnanadesikan, William D. Pearse, Allison K. Shaw

Bibliographic record

VenueEcology and Evolution · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsMcGill UniversityUniversité du Québec à Montréal
FundersNational Science Foundation
KeywordsForagingPredationBiologyEcologyForageHabitatEcosystem servicesEcosystemGeography

Abstract

fetched live from OpenAlex

Many organisms migrate between distinct habitats, exploiting variable resources while profoundly affecting ecosystem services, disease spread, and human welfare. However, the very characteristics that make migration captivating and significant also make it difficult to study, and we lack a comprehensive understanding of which species migrate and why. Here we show that, among mammals, migration is concentrated within Cetacea and Artiodactyla but also diffusely spread throughout the class (found in 12 of 27 orders). We synthesize the many ecological drivers of round-trip migration into three types of movement-between breeding and foraging sites, between breeding and refuge sites, and continuous tracking of forage/prey-each associated with different traits (body mass, diet, locomotion, and conservation status). Our results provide only partial support for the hypothesis that migration occurs without phylogenetic constraint. Furthermore, our findings suggest that categorizing migration into these three types may aid predictions of migrants' responses to environmental changes.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.013
GPT teacher head0.231
Teacher spread0.218 · 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 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

Citations41
Published2017
Admission routes1
Has abstractyes

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