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Record W2188883652 · doi:10.21273/hortsci.47.2.205

Velvet Bentgrass and Creeping Bentgrass Growth, Rooting, and Quality with Different Root Zone Media and Fertility Regimes

2012· article· en· W2188883652 on OpenAlexaff
John Robert Andrew Keith Watson, François Hébert, E.M. Lyons, Theo J. Blom, K.S. Jordan

Bibliographic record

VenueHortScience · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicTurfgrass Adaptation and Management
Canadian institutionsUniversity of GuelphMinistère des Ressources naturelles et des Forêts (Québec)
Fundersnot available
KeywordsAgrostis stoloniferaShootAgrostisDry weightVelvetAgronomyBiologyNitrogenPeatRelative growth ratePhosphorusHorticultureAnimal sciencePoaceaeGrowth rateChemistryMathematicsEcology

Abstract

fetched live from OpenAlex

Two complementary greenhouse studies were conducted to examine the effects of different root zones and fertilization regimes on ‘SR7200' velvet bentgrass ( Agrostis canina L.) and L-93 creeping bentgrass ( Agrostis stolonifera L.). In the first study, in which only velvet bentgrass was studied, peat content in the root zone mixture contributed significantly to initial establishment of this species and high seeding rates increased cumulative shoot dry weight early in establishment but became less significant as the turfgrass matured. Higher phosphorus rates contributed to increased cumulative shoot dry weight over the first 4 weeks of the experiment. Nitrogen rate was the most significant factor positively affecting both cumulative shoot dry weight and turfgrass quality. In the second experiment with both velvet bentgrass and creeping bentgrass, nitrogen rate significantly increased turfgrass quality when measured at Week 5, halfway through the experiment. Over time, however, turf growth and quality were negatively impacted in both species with increasing nitrogen rates. Root zone composition had a significant effect on initial establishment of both bentgrasses with greater peat content leading to higher quality early on. Cumulative shoot dry weight increased with increasing nitrogen rate but at higher rates, there was a concomitant decrease in root production.

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)0.001
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 score0.008
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.021
GPT teacher head0.239
Teacher spread0.218 · 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

Citations4
Published2012
Admission routes1
Has abstractyes

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