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Record W2040386148 · doi:10.1080/09640568.2012.684458

A multi-scale framework for evaluating the benefits and costs of alternative management strategies against invasive plants

2012· article· en· W2040386148 on OpenAlexaff
Leonardo Frid, Duncan Knowler, Judith H. Myers, L. K. Scott, Carol Murray

Bibliographic record

VenueJournal of Environmental Planning and Management · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBiological Control of Invasive Species
Canadian institutionsUniversity of British ColumbiaSimon Fraser University
FundersOregon Department of Agriculture
KeywordsScale (ratio)Risk analysis (engineering)Environmental resource managementEnvironmental economicsComputer scienceEnvironmental planningBusinessEconomicsEnvironmental scienceGeography

Abstract

fetched live from OpenAlex

Using a bioeconomic model that explicitly accounts for inventory and treatment expenditures, we carry out benefit-cost analyses of management strategies for three invasive plants in British Columbia: hawkweed, Scotch broom and Eurasian watermilfoil. For hawkweed, a province-wide biocontrol programme could achieve greater benefits than a conventional control programme, while for Scotch broom a small-scale mechanical treatment programme applied in a transport corridor was not economically viable unless it prevented spread into the surrounding area. Mechanical treatment of Eurasian watermilfoil in regional lakes generates net benefits to society, but inventory should be a key component of a control programme. Based on these analyses, we recommend continued development of successful biological control programmes for hawkweed and other invasive plant species.

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)0.003
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0030.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0090.000

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 head0.063
GPT teacher head0.285
Teacher spread0.221 · 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

Citations9
Published2012
Admission routes1
Has abstractyes

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