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Evaluation of Openers for Seeding Meadow Brome Grass (Bromus riparius) Using Air Delivery Seeding Systems

2005· article· en· W2801838988 on OpenAlexaffabout
D. H. McCartney, G. Hultgreen, Allan Boyden

Bibliographic record

VenueJournal of Range Management · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicTurfgrass Adaptation and Management
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsSeedingSeederAgronomySowingSeedlingEnvironmental scienceMathematicsBiology

Abstract

fetched live from OpenAlex

There is interest in Canada in seeding grass seed using air seeders and air drills that were originally designed for seeding cereals and oilseeds. These seeders use an air delivery system to move the seed from large grain tanks on the seeder to the cultivator furrow openers for seed placement in the ground. Various types of furrow openers (i.e. spoons or knives) were evaluated for their effectiveness in placing meadow brome grass seed (Bromus riparius [Rehmann]) in the ground. Knife openers provided the best seed emergence results. Seed brakes and variable air velocities were also evaluated as a means of preventing the seed from blowing out of the seed row when using high air velocities. The screen-type seed brakes were prone to plugging with the grass seed. Acceptable seeding results were achieved without seed brakes when used at low air velocities; however, at these lower air velocities, seed distribution may be less accurate. It was also shown that when monoammonium phosphate (11-51-0) was mixed with the meadow brome grass seed at 33 kg ha-1 as a means of preventing seed bridging in the delivery system, the seedling emergence counts were significantly less than applying the fertilizer at the point where the seed enters the openers.

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)0.001
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.070
GPT teacher head0.298
Teacher spread0.228 · 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
Published2005
Admission routes2
Has abstractyes

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