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Record W1989378319 · doi:10.4141/p01-149

Competitive ability of hybrid and open-pollinated canola (<i>Brassica napus</i>) with wild oat (<i>Avena fatua</i>)

2002· article· en· W1989378319 on OpenAlexafffundvenue
Hugh J. Beckie

Bibliographic record

VenueCanadian Journal of Plant Science · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaGovernment of Canada
KeywordsCanolaAvena fatuaBrassicaBiologyAgronomyCultivarWeedCompetition (biology)Shoot

Abstract

fetched live from OpenAlex

The competitiveness of three hybrid and three open-pollinated canola cultivars against two wild oat populations was determined under controlled environment conditions at two plant densities and five canola:wild oat ratios (100:0, 75:25, 50:50, 25:75, 0:100). Analysis of replacement series and derivation of relative crowding coefficients (RCC), based on shoot dry weight or leaf area, indicated that hybrid canola cultivars were twice as competitive than open-pollinated cultivars when weed interference was relatively high (i.e., high plant density and vigorous wild oat growth). Little difference in competitiveness among cultivar types was apparent when weed interference was lower. The results of this study suggest that hybrid canola cultivars may be best suited for use in an integrated weed management program, particularly for farmers of organic or low input cropping systems. Key words: Hybrid canola, Brassica napus, Avena fatua, replacement series, competition

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.199
Teacher spread0.177 · 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 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

Citations76
Published2002
Admission routes3
Has abstractyes

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