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Record W7037573557

Effect of Grass-White Clover Mixtures on Steer Performance and Sward Characteristics in Atlantic Canada

2024· article· en· W7037573557 on OpenAlexaboutno aff

Bibliographic record

VenueUKnowledge (University of Kentucky) · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicHealth, Education, and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPasturePerennial plantLolium perenneTrifolium repensStolonTiller (botany)GrazingDry matter
DOInot available

Abstract

fetched live from OpenAlex

Pasture production in winter cold regions such as Atlantic Canada is limited by the availability of winter hardy and productive grass and legume species, Perennial ryegrass (Lolium perenne L.), meadow fescue (Festuca prarensis Huds.) and timothy (Phleum pratense L.) grown in binary mixtures with white clover (Trifolium repens L.), and naturalised pasture consisting of Poa spp., Agrostis spp. and white clover, were compared under grazing, Steers were used to graze the swards from 16-26 cm down to 8 or 11 cm post-grazing surface heights, Dry matter intake was higher for natural pasture than for sown pastures, Animal gains were greatest for perennial ryegrass­white clover and lowest for the natural pasture, On timothy-white clover pasture the animal gains declined in the second season which coincided with poor persistence of timothy. Animal gains per ha were similar for 8 and 11 cm surface heights. Tiller densities of meadow fescue and timothy were very low and that of perennial ryegrass reached only 8000/m2, The stolon length of white clover varied considerably among mixtures. Breeding of hardy pasture cultivars in winter cold regions is essential for improved pasture productivity.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score0.759

Codex and Gemma teacher scores by category

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

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 head0.007
GPT teacher head0.238
Teacher spread0.231 · 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 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

Citations2
Published2024
Admission routes1
Has abstractyes

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