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Record W2078543328 · doi:10.4141/p03-065

Compositional changes over four years for binary mixtures of grass species grown with white clover

2005· article· en· W2078543328 on OpenAlexafffundvenue
D. B. McKenzie, Y. A. Papadopoulos, K. B. McRae, E. M. Butt

Bibliographic record

VenueCanadian Journal of Plant Science · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsGovernment of Newfoundland and LabradorAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsAgronomyDactylis glomerataBiologyGrazingGrowing seasonDry matterBiomass (ecology)Red CloverTrifolium repensPerennial plantForageFestuca rubraPoaceae

Abstract

fetched live from OpenAlex

Kentucky bluegrass, meadow fescue, orchardgrass, tall fescue, timothy, and reed canarygrass were seeded in all possible two-grass combinations with white clover in conventional and underseeded barley treatments using a split-plot design at the Western Agriculture Centre near Pynn’s Brook, NL. The objectives were: (1) to assess dry matter yield (DMY) of two binary grass species when sown with white clover in mixtures under a system with cuttings at similar crop growth stages as rotational grazing and to assess the effect of underseeding to barley on this system; (2) to identify mixtures that enhance herbage distribution throughout the grazing season; and (3) to assess the sward dynamics over successive cropping seasons. The composition of the binary grass mixtures with white clover affected seasonal DMY, seasonal herbage distribution, and sward dynamics over the production years. Orchardgrass in mixtures decreased DMY, shifted the herbage distribution toward early season, and competed with other species. Timothy composition of the stand showed the largest decline over the 3 production years, whereas white clover declined in mixtures with bluegrass, orchardgrass, or tall fescue. Meadow fescue and reed canarygrass with white clover was the most productive mixture with excellent persistence and good yield distribution over the growing season. Orchardgrass was the least compatible species in the mixtures; it dominated first growth and contributed the least to biomass production in later years. Both bluegrass and reed canarygrass performed well in mixtures over the 3 production years; bluegrass appeared to enhance the performance of the other species during summer regrowth whereas reed canarygrass was superior in the later part of the growing season. Underseeding with barley did not affect white clover yield in any production year but detrimentally affected the yield of orchardgrass and meadow fescue in mixtures, and their seasonal distribution. Key words: Bluegrass, orchardgrass, meadow fescue, tall fescue, timothy, reed canarygrass, repeated measurements, principal component analysis, herbage DM distribution, species 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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.023
GPT teacher head0.209
Teacher spread0.186 · 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 designObservational
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

Citations8
Published2005
Admission routes3
Has abstractyes

Explore more

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