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Record W7006090294

Sward Height in Grazing Management: Vertical Profiles in Forage Quality

2024· article· en· W7006090294 on OpenAlexaboutno aff

Bibliographic record

VenueUKnowledge (University of Kentucky) · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtist diversity and phylogeny
Canadian institutionsnot available
Fundersnot available
KeywordsGrazingQuadratForageYield (engineering)Organic matterPasture
DOInot available

Abstract

fetched live from OpenAlex

Vertical and temporal trends in herbage yield and quality were assessed in a study sown in 1989 near Elora, Ontario. In a replicated field trial with 0.1 ha paddocks, Hereford heifers rotationally grazed 2 swards to each of 2 residual grazing heights, namely, SO and 100 mm, with a requisite 200-2S0 mm entry height. Profiles in yield and in in vitro organic mailer digestibility (IVOMD) were developed from 6, 1500 cm2 quadrats per paddock, which were subjected to vertically stratified clipping, using sheep shears with a vacuum attachment. In 1990, obliging entry. at 200-2S0 mm stabilised herbage organic matter on offer, but IVOMD nonetheless declined seasonally, in all sward strata, by a weighted average of 10 percentage points, The vertical distribution of OM was sharply skewed In both swards, with yield in each stratum significantly greater than that above it, while IVOMD differed only among the three lowest strata. Sward height has revealed promising insights into the vertical array of herbage quantity and quality, which should prove directly useful to Ontario graziers.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.341

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 head0.012
GPT teacher head0.242
Teacher spread0.229 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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