MétaCan
Menu
Back to cohort
Record W2991920038 · doi:10.5539/jas.v12n1p58

Biometry of the Characteristics of Cajazeira (Spondias mombin L.) Stone in Northeast Brazil

2019· article· en· W2991920038 on OpenAlexvenueno aff
Janilson Pinheiro de Assis, Roberto Pequeno de Sousa, Paulo César Ferreira Linhares, Eudes de Almeida Cardoso, José Aluísio de Araújo Paula, Lunara de Sousa Alves, Maria Francisca Soares Pereira, Cydianne Cavalcante da Silva, Glenda Soares de Lira Rosado Nogueira, Misael Bruno de Araujo Silva

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Management and Crop Yield
Canadian institutionsnot available
Fundersnot available
KeywordsAnacardiaceaeRange (aeronautics)MathematicsGeographyHorticultureBiologyMaterials science

Abstract

fetched live from OpenAlex

The cajazeira (Spondias mombin L.) is a stone tree belonging to the Anacardiaceae family is very common in the caatinga ecoregion of northeastern of Brazil. This study assessed the biometry of cajazeira stones stones. The stones were collected in 2019 within an area of native vegetation in the campus of the Federal Rural University of the Semi-arid Region (UFERSA), Mossoró-RN. They were then taken to the Plant Science Laboratory to measure the following characteristics: length, width, length/width ratio, stones thickness, and weight. The variables length, width, length/width ratio, thickness, and weight of the stones had a low range of variation and low values for relative variation, and therefore high coefficients of Pearson of correlation. The data of length, width, and thickness showed a moderate degree of symmetry and a symmetrical and mesocurtic distribution, while length/width ratio and stones weight had almost symmetrical and mesocurtic distributions. The variables length and width and width and thickness showed significant positive linear correlations. The biometric data of caja stones fitted in to the approximate normal distribution of probability.

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 score0.587
Threshold uncertainty score0.163

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 science0.0010.000
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 head0.009
GPT teacher head0.215
Teacher spread0.206 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural ScienceSame topicSoil Management and Crop YieldFrench-language works237,207