MétaCan
Menu
Back to cohort
Record W2017514465 · doi:10.5539/jas.v5n4p179

Effect of Hot Air Oven and Microwave Oven Drying on Production of Quality Dry Flowers of Dutch Roses

2013· article· en· W2017514465 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Agricultural Science · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFlowering Plant Growth and Cultivation
Canadian institutionsnot available
Fundersnot available
KeywordsMicrowave ovenSilica gelHorticultureMathematicsTexture (cosmology)CultivarMaterials scienceBotanyFood scienceChemistryComposite materialMicrowaveBiologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The present investigation was conducted to evaluate different oven drying methods for obtaining better quality dried flowers of four Dutch rose cultivars viz., Skyline, Lambada, Ravel’ and First Red. Flowers dried at 40°C in hot air oven with silica gel were more acceptable for colour (3.48), appearance (3.50) and texture (3.23). Flowers dried by non-embedding method took least time (52.32 hours) for drying compared to embedded method. Flowers of ‘Lambada’ dried without embedding took least time for drying (52.07 hours) in hot air oven compared to other cultivars. Quality parameters such as colour (3.48), appearance (3.51) and texture (3.29) were superior in flowers dried for 2.5 minutes in microwave oven by embedding in silica gel. Flowers of ‘Lambada’ dried for 2.5 minutes by embedding in silica gel were best for overall acceptability, while unacceptable quality was obtained in case of flowers dried without any embedding medium. With respect to mode of desiccation, embedded drying was best for quality parameters viz., colour (2.92), appearance (2.81) and texture (2.55); however, non-embedding methods were least acceptable for quality parameters. Flowers of cv. ‘Lambada’ dried by embedding in silica gel yielded best quality dried flowers as it scored maximum point for all the quality parameters studied.

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.

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)0.001
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 score0.511
Threshold uncertainty score0.142

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.229
Teacher spread0.218 · 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