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Record W4414088835 · doi:10.1111/icad.70014

Restoration and rescue in an age of extinction: Translocation and reintroduction of insects and other arthropods

2025· article· en· W4414088835 on OpenAlexaff
Nusha Keyghobadi, Jaret C. Daniels

Bibliographic record

VenueInsect Conservation and Diversity · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsWestern University
Fundersnot available
KeywordsContext (archaeology)Biological dispersalChromosomal translocationDocumentationInsectDissemination

Abstract

fetched live from OpenAlex

Abstract Translocation is the intentional movement of organisms for conservation purposes, including species reintroductions and augmentation of declining populations. There is growing interest in insect translocation, and our understanding of best practices is rapidly developing. Relative to vertebrates, which have been the foci of most translocation programmes, insects and other arthropods provide both distinctive challenges and under‐explored opportunities. This special issue of Insect Conservation and Diversity explores some of the insect translocation efforts taking place globally. The papers in this special issue include translocations at various stages of progress and across diverse taxa and geographic regions. They address many key topics in insect translocation, including the critical role of ex situ rearing and breeding, disease monitoring and control, landscape context and dispersal ability, post‐translocation monitoring and the human context of translocation programmes. The papers illustrate common challenges faced by insect translocation programmes and provide new solutions and approaches, ranging from technical methods for disease monitoring in captive populations to comprehensive frameworks for planning. The idiosyncrasies of individual translocation programmes and the need to prioritize management goals can present challenges to disseminating the results of translocation programmes in traditional scientific venues. Nonetheless, more consistent documentation and dissemination of translocation efforts and outcomes will be important to advance the field.

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)0.004
metaresearch head score (Gemma)0.005
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: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.024
GPT teacher head0.232
Teacher spread0.209 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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