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Record W3043848792

EFFECTS OF PRE-PLANTING INCORPORATION OR POST-PLANTING TOP-DRESSING OF ORGANIC AMENDMENTS ON BERMUDAGRASS FOR TOLERANCE TO BELONOLAIMUS LONGICAUDATUS

2020· article· en· W3043848792 on OpenAlexaboutno aff
W. B. Jones, Jason Kruse, Heather A. Enloe, William T. Crow

Bibliographic record

VenueNematropica · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicTurfgrass Adaptation and Management
Canadian institutionsnot available
Fundersnot available
KeywordsSowingAgronomyCompostSoil conditionerAmendmentBiologySoil waterEcology
DOInot available

Abstract

fetched live from OpenAlex

The addition of organic amendments can improve several aspects of the soil environment, thereby improving tolerance to plant-parasitic nematodes and, in some cases, suppressing plant-parasitic nematodes.  Two organic amendments commonly used in golf and sports turf in the United States are locally produced composts and Canadian sphagnum peat moss (CSPM). Two field trials were conducted to evaluate the impacts of these organic amendments on turf health and suppression of sting nematode, Belonolaimus longicaudatus, on bermudagrass athletic turf.  One trial evaluated the effects of pre-planting incorporation of either compost or CSPM with soil to create a 20:80 amendment:soil mixture in the turf root zone. Another trial evaluated two kinds of compost blended with sand top-dressed onto the surface of established turf. Both trials evaluated effects on population density of B. longicaudatus, and on turf percent green cover.  Pre-planting incorporation of organic amendments suppressed B. longicaudatus but top-dressing did not.  Addition of composts by either pre-planting incorporation or blending with top-dressing improved turf percent green cover and, therefore, enhanced tolerance to B. longicaudatus.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score0.444

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 head0.011
GPT teacher head0.239
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 teacher head, 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

Citations2
Published2020
Admission routes1
Has abstractyes

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