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Record W3133072747 · doi:10.1139/cjps-2020-0258

Volunteer <i>Brassica napus</i> (L.) interference with soybean [<i>Glycine max</i> (L.) Merr.]: management thresholds, plant growth, and seed return

2021· article· en· W3133072747 on OpenAlexaffvenueabout
Paul Gregoire, Jonathan D. Rosset, Robert H. Gulden

Bibliographic record

VenueCanadian Journal of Plant Science · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBrassicaVolunteerCanolaSowingAgronomyWeedWeed controlGlyphosateBiologyGlycineGrowing seasonCropBrassica rapa

Abstract

fetched live from OpenAlex

Canola (Brassica napus L.) and soybean [Glycine max (L.) Merr.] are currently two of the three most common crops grown in Manitoba, which comprises the eastern regions of the Canadian Prairies. Volunteer B. napus is a prominent weed in soybean in Manitoba and glyphosate-resistant (GR) volunteer B. napus often is the only weed remaining after in-crop weed control with glyphosate in soybean. Additive-series field experiments were established at three locations in Manitoba in 2012 and 2013 to study volunteer B. napus interference with soybean and develop action and economic thresholds for this weed. Soybean were planted in narrow (25 cm) or wide (75 cm) row spacing and glyphosate-resistant B. napus seed was broadcast at densities of 0, 10, 20, 40, 80, 160, 320, and 640 seeds·m −2 at the time of soybean planting. Development of soybean and volunteer B. napus were determined throughout the growing season and seed yield of both species was determined at their respective physiological maturity. Volunteer B. napus is highly competitive with soybean, as action (&lt;9 plants·m −2 ) and economic (&lt;5 plants·m −2 ) thresholds were low. At these action thresholds, volunteer B. napus seed return to the weed seedbank was on average 14 400 seeds·m −2 and 10 400 seeds·m −2 in narrow- and wide-row soybean, respectively.

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 score0.905
Threshold uncertainty score0.943

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 science0.0010.000
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 head0.010
GPT teacher head0.179
Teacher spread0.169 · 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

Citations5
Published2021
Admission routes3
Has abstractyes

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