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Record W1993536791 · doi:10.5539/jas.v2n3p61

Post Harvest Physical and Nutritional Properties of Two Apple Varieties

2010· article· en· W1993536791 on OpenAlexvenueno aff
Abbas Gorji Chakespari, Ali Rajabipour, Hossein Mobli

Bibliographic record

VenueJournal of Agricultural Science · 2010
Typearticle
Languageen
FieldEngineering
TopicAgricultural Engineering and Mechanization
Canadian institutionsnot available
Fundersnot available
KeywordsSphericityTitratable acidMathematicsStatic frictionHorticultureWater contentVolume (thermodynamics)MoistureCoefficient of frictionChemistryFood scienceBotanyMaterials scienceGeometryComposite materialBiologyThermodynamicsPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

In this research, physical and nutritional properties of two Iranian apple varieties (Golab Kohanz, Shafi Abadi) were determined and compared. The physical properties were average fruit length, width and thickness, geometric, arithmetic and equivalent mean diameters, projected area, surface area, sphericity index, aspect ratio, fruit mass, volume, bulk and fruit densities and coefficient of static friction and the nutritional properties were PH, titratable acidity and total soluble solids. Average moisture content of the Golab Kohanz (GK) and Shafi Abadi (SA) varieties were 86% and 84% (w.b.), respectively. Based on statistical analysis, the properties were statistically different at 1% and 5% levels of significance for both varieties. However, the differences between the two studied varieties in the case of the aspect ratio, coefficient of static friction on various surfaces and PH were not significant (P>0.05).

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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.005
GPT teacher head0.177
Teacher spread0.172 · 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

Citations15
Published2010
Admission routes1
Has abstractyes

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