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Record W2808069886 · doi:10.7939/r3fx4q

Forage Responses to Herbicide Weed Control in Grass-Legume Swards

2011· article· en· W2808069886 on OpenAlexaboutno aff
Erin M. McLeod

Bibliographic record

VenueUniversity of Alberta Library · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsnot available
Fundersnot available
KeywordsAgronomyForageWeed controlLegumeWeedBiologyClopyralid

Abstract

fetched live from OpenAlex

Two field studies assessed sward dynamics to legume removal with and without Canada thistle and other broadleaf plants (i.e. forbs). When grown in mixtures with grass, alfalfa had a more consistent negative yield response to legume removal compared to clover swards. Within established pastures, total forage (i.e. legume and grass) had little association with Canada thistle, but was instead associated with perennial forbs such as dandelion. Grass responses (biomass and protein yield) in established swards were unable to compensate for legume removal up to 2 years after spraying. Relative yield ratios were used to identify weed and legume thresholds, and indicated the removal of legume and Canada thistle did not always negatively impact forage production. Instead, select positive yield responses were observed depending on the initial composition, growing conditions and abundance of weed and legume.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

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 head0.018
GPT teacher head0.181
Teacher spread0.164 · 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

Citations2
Published2011
Admission routes1
Has abstractyes

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