MétaCan
Menu
Back to cohort
Record W4282973572 · doi:10.21203/rs.3.rs-1762292/v1

The ecological dimension of global trade: origin and recipient regions of biological invasion costs

2022· preprint· en· W4282973572 on OpenAlexaff
Emma J. Hudgins, Ross N. Cuthbert, Phillip J. Haubrock, Nigel A. S. Taylor, Melina Kourantidou, Dat Tien Nguyen, Alok Bang, Anna J. Turbelin, Desika Moodley, Elizabeta Briski, Syrmalenia G. Kotronaki, Franck Courchamp

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsMcGill UniversityCarleton University
FundersAXA Research FundAkademie Věd České RepublikyAgence Nationale de la RechercheGrantová Agentura České RepublikyLeverhulme TrustBiodiversa+Alexander von Humboldt-Stiftung
KeywordsDimension (graph theory)EcologyGeographyEconomic geographyBiologyMathematics

Abstract

fetched live from OpenAlex

Abstract Globalization challenges sustainability by intensifying the ecological and economic impacts of biological invasions. These impacts may be unevenly distributed worldwide, with costs disproportionately incurred by a few regions. Here, we identify how invasion economic costs are distributed among origin and recipient regions at country and continent levels, and determine socio-economic and biodiversity-related predictors of invasion cost dynamics. Flows of invasive alien species causing costs originated from several regions, most frequently flowing to Europe, whereas monetary costs predominantly flowed from Asia to North America. High cost flows between countries were related to various environmental and socio-economic factors, such as shared biomes, high GDP and a common language. This characterization of ‘sender’ and ‘receiver’ regions of invasive alien species and their associated cost can inform biosecurity planning and the prioritization of control efforts across invasion routes, to achieve more sustainable economies and societies, while protecting biodiversity.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.139
GPT teacher head0.409
Teacher spread0.270 · 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 designSimulation or modeling
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

Citations3
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueResearch SquareSame topicAnimal Ecology and Behavior StudiesFrench-language works237,207