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Record W2792865085 · doi:10.5539/jas.v10n4p223

Micronutrient Content and Physiological Quality of Soybean Seeds

2018· article· en· W2792865085 on OpenAlexvenueno aff
Geliandro Anhaia Rigo, Luís Osmar Braga Schuch, Rodrigo Lamaison de Vargas, Willian Silva Barros, Vinícius Jardel Szareski, Ivan Ricardo Carvalho, Cristian Troyjack, João Roberto Pimentel, Ruddy Alvaro Veliz Escalera, Tiago Corazza da Rosa, Velci Queiróz de Souza, Tiago Zanatta Aumonde, Tiago Pedó

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Micronutrient Interactions and Effects
Canadian institutionsnot available
Fundersnot available
KeywordsMicronutrientMolybdenumManganeseZincChemistryCopperCultivarHorticultureAgronomyFood scienceBiologyInorganic chemistry

Abstract

fetched live from OpenAlex

The aimed to correlate the micronutrients content in soybean seeds with their physiological potential. The work was developed in the Federal University of Pelotas, in the facilities of the Seed Science and Technology Graduate Program. The experimental design was randomized blocks in arranged in four replicates. The micronutrients measured were: B, Cu, Fe, Mn, Mo, Zn, Al and Na. The magnitudes of micronutrients are dependent on the genetic constitutions of soybean cultivars. Higher variations are expressed for boron, copper, manganese, zinc, molybdenum, sodium and aluminum content, while iron is the most stable micronutrient in soybean seeds. Molybdenum and copper are characterized as determining micronutrients for physiological quality of soybean seeds.

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 score0.804
Threshold uncertainty score0.215

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.064
GPT teacher head0.275
Teacher spread0.211 · 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

Citations16
Published2018
Admission routes1
Has abstractyes

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