MétaCan
Menu
Back to cohort
Record W2891593956 · doi:10.5539/jas.v10n10p163

Crambe Cake to Meloidogyne javanica Control in Lettuce

2018· article· en· W2891593956 on OpenAlexvenueno aff
Júlio César Antunes Ferreira, Olívia Diulen Costa Brito, Paula Juliana Grotto Débia, Beatriz de Almeida Silva, Guilherme Tarini, Cláudia Regina Dias‐Arieira

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNematode management and characterization studies
Canadian institutionsnot available
Fundersnot available
KeywordsCrambeAgronomyBiologyMeloidogyne javanicaInoculationHorticultureNematode

Abstract

fetched live from OpenAlex

Crambe is an oilseed, which pressing for oil extraction results in the waste called crambe cake. The aforementioned waste may present potential to control nematodes, since it derives from brassica species. The aim of the current study is to assess the best crambe cake application to control Meloidogyne javanica in lettuce plants. Five experiments were carried out in a greenhouse by adopting different crambe cake application procedures; each experiment comprised five treatments (0 (control), 5; 10; 15; 20 g crambe cake per 1 L soil). Lettuce seedlings were cultivated in soil treated with crambe cake, and inoculated with 5,000 nematode eggs and occasional juveniles (J2). Nematological and vegetative parameters were assessed 45 days after inoculation. Nematode reduction was observed in the experiment that applied doses close to 15 g crambe cake to the soil surface; nematode control recorded 83 and 68% for eggs and J2 total and per root gram, respectively. The same parameters showed up to 82 and 93% reduction when the cake was incorporated to the first 8 cm deep into the soil. The number of eggs and J2 per root system reduced by 93% when the cake was incorporated to the total soil volume. Overall, the crambe cake did not increase plant development; in some cases, phytotoxicity was observed at the highest doses.

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 score0.979
Threshold uncertainty score0.198

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 studies0.0000.000
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 head0.013
GPT teacher head0.229
Teacher spread0.217 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural ScienceSame topicNematode management and characterization studiesFrench-language works237,207