MétaCan
Menu
Back to cohort
Record W2738057567 · doi:10.5539/jas.v9n8p167

Resistance Evaluation of the Acerola (Malphigia emarginata D.C.) Seed to Compression

2017· article· en· W2738057567 on OpenAlexvenueno aff
Ácacio Figueirêdo Neto, Marcos Antônio da Silva Irmão, Jean Philippe Santos Gherardi de Alencar, Raimunda Carneiro

Bibliographic record

VenueJournal of Agricultural Science · 2017
Typearticle
Languageen
FieldEngineering
TopicAgricultural Engineering and Mechanization
Canadian institutionsnot available
FundersFundação de Amparo à Pesquisa do Estado da Bahia
KeywordsCompression (physics)Water contentMoistureDeformation (meteorology)ModulusMathematicsMaterials scienceTangent modulusComposite materialAngle of reposeGeotechnical engineeringGeology

Abstract

fetched live from OpenAlex

The objectives of this work were to verify the moisture content influence on the maximum compression force values, to determine the Proportional Modulus of Deformation, the Maximum Tangent and Secant for acerola seeds under compression on its natural repose position and for fixed deformations. Acerola seeds with moisture content varying from 0.12 to 0.46 (d.b.) compressed uniaxially between two parallel rigid plates. It can be concluded that the compression needed for deforming the acerola seeds decreases as its moisture content increases when the deformation values were within 19.2 and 548.8 N. The Proportional Modulus of Deformation increases with the reduction of the moisture content, where values found were within 5.2 to 72.1 × 107 Pa. The sigmoidal model represented resistance to the compression of the acerola seeds adequately for different moisture content.

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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.245
Teacher spread0.231 · 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

Explore more

Same venueJournal of Agricultural ScienceSame topicAgricultural Engineering and MechanizationFrench-language works237,207