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Record W4413378575 · doi:10.32942/x2rd2b

Parallel concepts and future opportunities across the biological control and invasion sciences

2025· article· en· W4413378575 on OpenAlexfundno aff
Ross N. Cuthbert, Nompumelelo Catherine Baso, Tressia Chikodza, Candice Coombes, Jane Doherty, Michael M. Githae, M. C. Hernández, Michael Jukes, David Kinsler, Hugh J. MacIsaac, Hlumelo Mantshi, Reyard Mutamiswa, Anthony Ricciardi, Wade Sexton, Guy F. Sutton, Deric Tanka, Clarke J. M. van Steenderen, Jaimie T. A. Dick, Julie A. Coetzee

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBiological Control of Invasive Species
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaLeverhulme Trust
KeywordsControl (management)Biological sciencesPolitical scienceSociologyComputer scienceEngineering ethicsEngineeringBiologyArtificial intelligenceComputational biology

Abstract

fetched live from OpenAlex

The biological control and invasion sciences are long-standing research fields that have accrued enormous fundamental and applied interest. However, their theoretical and practical integration remains in its infancy. Utilizing an expert elicitation process with participants spanning these sciences, we identify conceptual parallels and future opportunities to strengthen links and address future challenges in both fields. We found that the biocontrol and invasion sciences face pervasive context-dependencies that must be understood to improve outcome predictions, including climatic changes, spatiotemporal scales, and ‘ecological surprises’. Both sciences would further benefit from terminological streamlining to improve communication, sharing of emerging technologies, and mitigation of the taxonomic decline. The two fields are strongly affected by social perceptions and awareness by decision makers, requiring more effective engagement and translation efforts. Our exercise promotes cross-cutting interdisciplinary advances to improve understanding of fundamental ecological and evolutionary processes, socio-ecological challenges, and management efficacy across the biocontrol and invasion sciences.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.729
Threshold uncertainty score0.714

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
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 head0.070
GPT teacher head0.283
Teacher spread0.213 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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