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Record W2587817598 · doi:10.5539/jas.v9n3p172

Different Treatments for Breaking Dormancy of Leucaena Seeds (Leucaena leucocephala)

2017· article· en· W2587817598 on OpenAlexvenueno aff
Tiago Neves Pereira Valente, Érico da Silva Lima, Bruno Borges Deminicis, Andréia Santos Cezário, Wallacy Barbacena Rosa dos Santos, Luana Almeida Souza, Vitória Gallo Borges de Lima

Bibliographic record

VenueJournal of Agricultural Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed Germination and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsLeucaena leucocephalaGerminationLeucaenaDormancyBiologySeed dormancySeed treatmentLegumeCompletely randomized designHorticultureSowingForageAgronomyBotany

Abstract

fetched live from OpenAlex

The objective of the study was to evaluate the influence of methods for breaking dormancy the seeds of tropical forage legume Leucaena leucocephala (Lam.). The seed treatments were: (T1) water at 100 ºC/10 min; (T2) water at 100 ºC/1 min; (T3) Acetone (10 min); (T4) Ethyl alcohol (10 minutes); and (T5) intact seeds (control). Data were analyzed using a completely randomized design with eight replications, and it was adopted the Tukey test at 5% significance level. The treatment T1, had the highest speed of germination of seeds GSI, differed (P < 0.05). The T5 treatment (control) was the slowest response, that treatments that passed through some break dormancy until the seventh day after the beginning of the test (Germ7), with an amount of 20% accumulation of germinated seeds. The worst result of germination it was T5, with 30% of non-germinated seeds after 15 days of sowing.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.280
Teacher spread0.251 · 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 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
Published2017
Admission routes1
Has abstractyes

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