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Record W2157922041 · doi:10.1017/s1466046609090012

Research Article: The Use of Domestic Goats and Vinegar as Municipal Weed Control Alternatives

2009· article· en· W2157922041 on OpenAlexafffundabout
Annie L. Booth, Norman W. Skelton

Bibliographic record

VenueEnvironmental Practice · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsUniversity of Northern British Columbia
FundersUniversity of British ColumbiaFederation of Canadian MunicipalitiesUniversity of Northern British Columbia
KeywordsThistleDandelionWeedCirsium arvenseWeed controlTaraxacum officinaleBiologyAgronomyInvasive speciesBiological pest controlBotany

Abstract

fetched live from OpenAlex

This article presents the results of a two year pilot case study of alternative weed control in a northern Canadian community. Investigators tested the efficacy of acetic acid (vinegar) and a domestic herbivore (goats) as invasive weed control alternatives to the use of commercial herbicides in a north central British Columbian municipal setting. Results were positive for using an 8% concentration of vinegar as a control for Canada thistle (Cirsium arvense (L.) scop.), although these results were significant only in the second year of applications. Domestic goats demonstrated significant interest in thistle, as well as hawkweed, (Hieracium spp.), two species of horsetail (Equisetum arvense and Equisetum pratense), oxeye daisies (Leucanthemum vulgare), and the common dandelion (Taraxacum officinale). Cost estimates suggest that over a five year period, both methods are as cost effective as single application herbicides, while posing fewer concerns over impacts on human and ecosystem health. Both are simple solutions easily implemented, with some planning, even by small municipalities and communities.

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)0.001
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 score0.843
Threshold uncertainty score0.249

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.072
GPT teacher head0.311
Teacher spread0.239 · 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

Citations6
Published2009
Admission routes3
Has abstractyes

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