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Record W2890920640 · doi:10.5539/jas.v10n10p197

Interference Periods of Weeds Infesting Maize Crop

2018· article· en· W2890920640 on OpenAlexvenueno aff
Leandro Galon, Maico André Michelon Bagnara, Ricardo Luis Gabiatti, Felipe José Menin Basso, Felipe Nonemacher, Luciane Renata Agazzi, Lauri Lourenço Radünz, César Tiago Forte

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsnot available
Fundersnot available
KeywordsAgronomyWeedRandomized block designCropWeed controlDigitariaBiologyYield (engineering)MathematicsPhysics

Abstract

fetched live from OpenAlex

When competing with crops, weeds interfere with their growth and consequently reduce grain yield. The purpose of this research was to determine the periods of interference; PIP (pre-interference period), TPWC (total period of weed control), and CPWC (critical period of weed control) of the weeds Alexandergrass (Urochloa plantaginea) and southern crabgrass (Digitaria ciliares) in maize. The experiment was conducted in a randomized complete block design with four replications, in a no-tillage system. The treatments consisted in maintaining maize in the presence and absence of Alexandergrass and southern crabgrass for increasing periods of 0, 7, 14, 21, 28, 35 and 42 days after emergence (DAE). Southern crabgrass and Alexandergrass weeds originated from the soil seed bank with an average density of 215 and 87 plants m-2, respectively. At the end of each period, PIP or TPWC, the weed and crop dry biomass was determined. At 42 DAE, the height and stem diameter of maize plants were evaluated. At harvest 10 maize plants per experimental unit were evaluated for length of ears, number of rows per ear, and number of grains per row. Yield was measured by taking three central rows from each experimental unit. The results indicate that the PIP was 17 DAE, the TPWC was 32 DAE, and the CPWC was 17 to 32 DAE.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.964
Threshold uncertainty score0.252

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.020
GPT teacher head0.249
Teacher spread0.229 · 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

Citations23
Published2018
Admission routes1
Has abstractyes

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