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Record W1975432043 · doi:10.4141/cjps09110

The Biology of Canadian weeds. 144. Pastinaca sativa L.

2010· article· en· W1975432043 on OpenAlexvenueaboutno aff
Nancy P. Cain, S. J. Darbyshire, A. Francis, Robert E. Nurse, Marie‐Josée Simard

Bibliographic record

VenueCanadian Journal of Plant Science · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and fungal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsWeedBiologyPerennial plantAgronomyCropWeed controlGlyphosate

Abstract

fetched live from OpenAlex

The parsnip, Pastinaca sativa, was introduced to North America shortly after European settlement as an important root-crop. It subsequently escaped cultivation and naturalized as a less palatable “wild” form. Cultivation of parsnip has diminished in Canada to the point where it is now only a minor crop, but the wild form has increased as a troublesome weed, particularly in eastern regions. Wild parsnip is most prevalent in eastern Canada and the northeastern United States, but occurs across the continent except in the far north and extreme southeast. As a monocarpic biennial with a large tap root, it reproduces entirely by seed. A wide variety of habitats and soil types are tolerated. It is considered a noxious weed because of its toxic properties (primarily photo-activated dermatitis) to both humans and livestock. It invades disturbed sites, rights-of-way, pastures, perennial crops, and reduced-tillage fields where it effectively out-competes shorter vegetation. In arable fields, wild parsnip is normally controlled by tillage. Manual removal, cutting, and mowing can be effective in reducing seed production, but direct contact with plants or sap is hazardous. Various herbicides have been reported to be useful in the control of wild parsnip (e.g., glyphosate, 2,4-D, triclopyr, etc.), but little quantitative information is available on application rates and levels of control.Key words: Panais sauvage, Pastinaca sativa, PAVSA, weed biology, wild parsnip

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score0.585

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.020
GPT teacher head0.208
Teacher spread0.188 · 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 designBench or experimental
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

Citations17
Published2010
Admission routes2
Has abstractyes

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