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Record W2482224220 · doi:10.1002/9781118392553.ch11

Societal values expressed through policy and regulations concerning biological control releases

2016· other· en· W2482224220 on OpenAlexfundaboutno aff
A. W. Sheppard, Keith Douglass Warner

Bibliographic record

Venuenot available
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicBiological Control of Invasive Species
Canadian institutionsnot available
FundersCanadian Food Inspection AgencyU.S. Department of AgricultureNational Science Foundation
KeywordsConvention on Biological DiversityBiosecurityBiodiversityChampionBiosafetyEnvironmental planningConference of the partiesInternational tradeControl (management)BusinessEnvironmental resource managementConventionGeographyPolitical scienceEnvironmental protectionEcologyBiologyEconomics

Abstract

fetched live from OpenAlex

The evolution of policy and regulations for the importation of live biological organisms across national and other jurisdictional borders, under which biological control agent introductions are regulated, has mirrored changes in societal values and concerns about such deliberate introductions. Five countries, including Australia, Canada, New Zealand, South Africa, and the United States have conducted the vast majority of the world's classical biological control agent introductions. Internationally, both Australia and New Zealand countries champion strong international biosecurity standards to reduce biosecurity risks from international trade. Many countries are harmonizing their goals with respect to reducing invasive species’ impacts on the environment through their joint commitments under the Convention on Biological Diversity (CBD). There are different complex processes regulating the release of weed, and insect biological control agents across countries. The development of the CBD decisions and targets around biodiversity protection led to the Nagoya Protocol concerning benefit-sharing of 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 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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.315
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0150.000

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 head0.047
GPT teacher head0.270
Teacher spread0.223 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations6
Published2016
Admission routes2
Has abstractyes

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