MétaCan
Menu
Back to cohort
Record W2785336564 · doi:10.5539/jas.v10n3p377

Electrical Conductivity Test to Evaluate the Physiological Quality of Salvia hispanica L. Seeds

2018· article· en· W2785336564 on OpenAlexvenueno aff
Aline Klug Radke, Diéli Witte Maass, Marjana Schellin Pieper, Andréa Bicca Noguez Martins, Rafael Oliveira Vergara, Francisco Amaral Villela, Géri Eduardo Meneghello

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPolysaccharides Composition and Applications
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsGerminationHorticultureLamiaceaeHerbaceous plantElectrical resistivity and conductivityBiologyBotanyEngineering

Abstract

fetched live from OpenAlex

Chia (Salvia hispanica L.) is an herbaceous plant that belongs to the Lamiaceae family. Seed vigor testing is an important component of quality control programs, and electrical conductivity test is a possible option in this process. The objective of this study was to identify a methodology of electrical conductivity test to stratify chia seed lots at vigor level according to the emergence of seedlings. Six lots of chia seeds were used in this study. The seeds were exposed to the following determinations: first germination count, germination, emergence speed index, emergence, aerial and root length, aerial and root dry matter, and electrical conductivity at 25, 50 and 75 mL during 1, 2, 4, 6, 8 and 24 hours of soaking in water. The electrical conductivity test in the combination of 25 seeds using 50 mL of water in 6-hour of soaking period, as well as the combination of 50 seeds using 50 mL of water for 24 hours of soaking, were efficient in the stratification of chia seeds in different levels of vigor.

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)0.001
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 score0.865
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.063
GPT teacher head0.324
Teacher spread0.262 · 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

Citations5
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural ScienceSame topicPolysaccharides Composition and ApplicationsFrench-language works237,207