MétaCan
Menu
Back to cohort
Record W2796856922 · doi:10.5539/jas.v10n5p319

Agronomic Performance and Multivariate Analysis Applied to Three-Waycross Maize Hybrids

2018· article· en· W2796856922 on OpenAlexvenueno aff
Tiago Corazza da Rosa, Ivan Ricardo Carvalho, Vinícius Jardel Szareski, Alan Júnior de Pelegrin, Maurício Horbach Barbosa, Nathan Löbler dos Santos, Tamires da Silva Martins, Adriel Somavilla Uliana, Velci Queiróz de Souza

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetics and Plant Breeding
Canadian institutionsnot available
Fundersnot available
KeywordsSpike (software development)HybridBiologyYield (engineering)Multivariate statisticsAgronomyGrain yieldMathematicsHorticultureMaterials scienceStatisticsComposite material

Abstract

fetched live from OpenAlex

The aim of this wok was to evaluate the agronomic performance of three-waycross maize hybrids grown in different environments, to determine linear associations and to employ multivariate analysis for the measured traits. The experimental design used was randomized blocks in factorial scheme, arranged in three replicates. The three-way cross maize hybrids evaluated evidence phenotypic variability for the traits spike diameter, spike length, number of rows with grains, number of grains per row, cob mass and spike grains mass. The growing environment of Campos Borges-RS favors the increment of spike diameter, number of grains per row, spike mass, cob diameter, cob mass, mass of a thousand grains, spike grains mass and grain yield. Significant interactions between three-way cross maize hybrids and growing environments are verified for plant height, spike insertion height and prolificity. The traits spike diameter, mass of a thousand grains and mass of grains per spike present positive correlation with maize grain yield. The distinction of three-way cross hybrids is based on spike insertion height, spike diameter, plant height and mass of a thousand grains. The hybrids 2B688 HX® and 2A55 HX® are genetically closer, according to the biometric approach of canonical variables.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.958
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
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 head0.017
GPT teacher head0.210
Teacher spread0.193 · 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 designObservational
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

Citations9
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural ScienceSame topicGenetics and Plant BreedingFrench-language works237,207