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Record W4402055852 · doi:10.1079/9781800623279.0050

<i>Convolvulus arvensis</i>L., Field Bindweed / Liseron des champs (Convolvulaceae)

2024· book-chapter· es· W4402055852 on OpenAlexaboutno aff
Ghislaine Cortat, A. S. McClay, Ivo Toševski, Rosemarie De Clerck-Floate, John F. Gaskin

Bibliographic record

VenueCABI eBooks · 2024
Typebook-chapter
Languagees
FieldAgricultural and Biological Sciences
TopicPlant Taxonomy and Phylogenetics
Canadian institutionsnot available
Fundersnot available
KeywordsConvolvulusConvolvulaceaeField (mathematics)BotanyBiologyMathematicsWeed

Abstract

fetched live from OpenAlex

Field bindweed, Convolvulus arvensis , is a weed of agricultural and horticultural ecosystems in Canada. It is a regulated noxious weed in several Canadian provinces that is difficult to manage; repeated herbicide treatments are required. Integrated approaches using tillage and competitive vegetation have been studied, as has biological control. Two arthropod biological control agents, Tyta luctuosa and Aceria malherbae , were first released before 2012, with variable levels of establishment and impact on C. arvensis in both Canada and the United States. Thus, interest in biological control of field bindweed was renewed, leading to the rejection of several agents (e.g., Longitarsus pellucidus and Longitarsus rubiginosus ) and identification of potential agents (e.g., Melanagromyza albocilia and Microsphecia brosiformis ). The chapter reviews the current status of biological control research targeting field bindweed.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.020
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.006

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 head0.038
GPT teacher head0.212
Teacher spread0.174 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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