MétaCan
Menu
Back to cohort
Record W2235732462

Tomato, pepper, and watermelon tolerance to EPTC applied under mulch in Florida

2008· article· en· W2235732462 on OpenAlexaboutno aff
Eugene McAvoy, William M. Stall

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Management Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCyperusMulchCyperus rotundusAgronomyWeedWeed controlPepperCropBiologyHorticulture
DOInot available

Abstract

fetched live from OpenAlex

For over 35 years, Florida tomato (Lycopersicum esculentum L.) growers have relied on methyl bromide for their soilborne pest, disease, and weed control problems. The use of methyl bromide as a soil fumigant is now being phased out under the Montreal Protocol. Yellow nutsedge (Cyperus esculentus L.) and purple nutsedge (Cyperus rotundus L.) are among the major weed control challenges in many tomato production systems. Since the leading alternative fumigants provide less than satisfactory control of nutsedge, Florida growers may have to consider the use of a preplant herbicide for control. EPTC (s-ethyl dipropylthiocarbamate) is an effective material that provides selective pre-emergent control of grasses, sedges, and many broadleaf weeds. Three years of small plot trials in Florida have shown that application of EPTC to the bed surface just prior to mulch application with a 14-day pre-transplant waiting period delivered excellent crop safety with very good nutsedge control. On-farm demonstration trials in Southwest Florida on tomato using EPTC applied to the bed and immediately covered with polyethylene fi lm also demonstrated excellent nutsedge control and had no apparent effect on the crop. Early indications are that EPTC may be an important tool in tomato weed management in the development of methyl bromide alternative strategies.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.826
Threshold uncertainty score0.185

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 head0.016
GPT teacher head0.191
Teacher spread0.175 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

Explore more

Same topicPlant Disease Management TechniquesFrench-language works237,207