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Record W7017735564

Chemical Trials for Dollar Spot Disease Control Greens Height Turf - Summer 2004

2021· other· en· W7017735564 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2021
Typeother
Languageen
FieldEnvironmental Science
TopicTurfgrass Adaptation and Management
Canadian institutionsnot available
Fundersnot available
KeywordsChlorothalonilFungicideChemical controlDisease controlInoculationIprodione
DOInot available

Abstract

fetched live from OpenAlex

Seven chemical and control treatments were evaluated on a 11 year old sward of Penncross7 creeping bentgrass (Agrostis palustris) at the Guelph Turfgrass Institute in Guelph, Ontario during July to October 2004 for control of dollar spot disease (caused by Sclerotinia homoeocarpa). The grass was maintained at greens height (5 mm). In addition to inoculated and uninoculated control treatments, a standard fungicide treatment, Daconil 2787 EC containing 40% chlorothalonil which is registered and recommended for control of dollar spot disease of turfgrass in Ontario was included. The treatments were applied over a 12-week period. Disease was monitored over a 13-week period. BAS 51004F 70 WG (3.14 g and 4.0 g - 14 days) and BAS 51004F 70 WG alternate with Insignia 20 WG (4.0 g alt. 28.0 g - 14 days) achieved excellent results 28 July onward. BAS 51004F 70 WG (5.57 g - 21-28 days) significantly reduced disease on 22 and 28 July and achieved excellent results for the duration on the trial. Daconil 2787 EC (190 mL - 14 days) achieved excellent control with the exception of 16 and 23 September. No phytotoxicity was observed throughout the trial.

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)0.000
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 score0.045
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.237
Teacher spread0.204 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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