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Record W2234264854 · doi:10.1614/ws-d-15-00076.1

Effect of Biennial Wormwood (<i>Artemisia biennis</i>) Interference on Sunflower Yield and Seed Quality

2015· article· en· W2234264854 on OpenAlexaffabout
Derek W. Lewis, Andrea Cavalieri, Robert H. Gulden

Bibliographic record

VenueWeed Science · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSunflower and Safflower Cultivation
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSunflowerAcheneSeedlingWeedAgronomyCropBiologyYield (engineering)Horticulture

Abstract

fetched live from OpenAlex

Biennial wormwood has been increasing in Manitoba, Canada, but information is limited on the potential of biennial wormwood to reduce crop yields. Field experiments were conducted over 5 site-yr throughout southern Manitoba in 2010 and 2011 to determine the effect of biennial wormwood density and relative time of biennial wormwood seedling recruitment on sunflower growth, development, yield, and seed quality. Biennial wormwood was broadcast on the soil surface at six densities into sunflowers planted in 75-cm rows, either at the same time the sunflower crop was planted (early weed seedling recruitment) or when the sunflowers were at about the four-leaf stage (late weed seedling recruitment). When biennial wormwood emerged at about the same time as the sunflowers, yield was reduced by up to 46%. Early-recruiting biennial wormwood had minimal effect on sunflower growth and development, but sunflower achene size and individual achene weight were reduced, even when no effect on sunflower yield was observed. Biennial wormwood plants that recruited after the four-leaf stage of the sunflower crop had no effect on sunflower yield or seed quality.

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)0.002
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.638
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.041
GPT teacher head0.283
Teacher spread0.242 · 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

Citations2
Published2015
Admission routes2
Has abstractyes

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