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Record W4384566005 · doi:10.56367/oag-039-10785

Stored fuel's importance for migrating monarch butterflies: Implications for conserving all migrant animals

2023· article· en· W4384566005 on OpenAlexaff
Keith A. Hobson

Bibliographic record

VenueOpen Access Government · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsEnvironment and Climate Change CanadaWestern University
Fundersnot available
KeywordsGeographyClimate changeMonarch butterflyEcologyBiology

Abstract

fetched live from OpenAlex

Stored fuel's importance for migrating monarch butterflies: Implications for conserving all migrant animals In his latest research, Keith A. Hobson, Research Scientist and Professor at Western University, explores why stored fuel is critical to migrating animals, such as monarch butterflies. Conserving migratory animals in a rapidly changing world requires we quickly and efficiently determine the most critical or vulnerable points in their annual cycles that typically involve numerous locations spread over hundreds to thousands of kilometers. Although we know migration routes or connections between breeding and wintering regions for many species of concern, how animals fuel their migration along migratory paths and how their nutritional needs are affected by various factors generally remains unknown. In times of current and predicted climate change, the added burdens of weather extremes add to the many threats facing migrants. So it is ever more urgent to ensure that our conservation efforts and funds are directed at the most critical locations temporally and spatially.

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)0.002
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.054
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.174
GPT teacher head0.412
Teacher spread0.238 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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