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Distribution and interference of dandelion (Taraxacum officinale) in spring canola

2003· article· en· W2173482696 on OpenAlexaff
Nathan T. Froese, Rene C. Van Acker

Bibliographic record

VenueWeed Science · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsDandelionTaraxacum officinaleCanolaTillageAgronomyBiology

Abstract

fetched live from OpenAlex

In both reduced-tillage and tilled fields, dandelion can be a problem, but the effect of dandelion on canola yield is unknown. This study was conducted to investigate the effect of dandelion infestation on spring canola yield and the influence of tillage on interference and in-field distribution of dandelion. Dandelion distribution was not associated with tillage regimen. Dandelion distribution showed some relationship to past cropping history, for example, the presence of alfalfa in the rotation. The strength of correlation between measures of dandelion infestation level and canola yield loss was associated with tillage regimen. For tilled fields, there was no correlation between reduction in canola yield and any measurements of dandelion infestation level. For reduced-tillage fields, the most reliable measures of dandelion interference level were dandelion ground cover prespray, total dandelion rosette diameter prespray, relative dandelion ground cover prespray, and total dandelion root diameter at crop harvest.

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)0.000
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 score0.973
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.223
Teacher spread0.207 · 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

Citations18
Published2003
Admission routes1
Has abstractyes

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