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Record W7112235546

Effect of Italian Ryegrass Establishment Methods of Yield, Herbage Quality and Soil Compaction

2025· article· W7112235546 on OpenAlexaboutno aff

Bibliographic record

VenueUKnowledge (University of Kentucky) · 2025
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicAgriculture, Soil, Plant Science
Canadian institutionsnot available
Fundersnot available
KeywordsSeedingLolium multiflorumLoamDry matterPastureYield (engineering)SeedbedNitrogen
DOInot available

Abstract

fetched live from OpenAlex

Italian rye grass (Lolium multiflorum Lam.) is a summer annual in the Atlantic Provinces of Canada and reseeding in spring is necessary for maintaining productive swards. Intensive cultivation and seeding method of Italian ryegrass was compared with four direct seeding techniques in four three-year experiments on a Charlottetown fine sandy loam soil, at two sites, on Prince Edward Island. Dry matter yields of ryegrass were similar for direct seeding and seeding cultivated seed bed for the first two years. Some yield advantage was recorded when direct seeded ryegrass followed barley in the third year. Total nitrogen concentration in tissue was similar for all treatments in the first year, but in the second and third years total N was generally greater with cultivation than with direct seeding. Although dry matter yield of permanent pasture was greater than that of ryegrass the nitrogen produced ha-1 was similar for both. Measurements of soil resistance, porosity, proportion of macro-pores (diameter> 50 µ,m) and pore continuity, used as indices of soil compaction, did not show any adverse effect of the seeding methods on soil structure.

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 score0.009
Threshold uncertainty score0.017

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 head0.025
GPT teacher head0.294
Teacher spread0.269 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueUKnowledge (University of Kentucky)Same topicAgriculture, Soil, Plant ScienceFrench-language works237,207