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Record W2975680061 · doi:10.1080/07373937.2019.1670672

Electrically enhanced drying of white champignons

2019· article· en· W2975680061 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDrying Technology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Inactivation Methods
Canadian institutionsDalhousie University
Fundersnot available
KeywordsElectrohydrodynamicsRelative humidityMaterials scienceVolumetric flow rateBrowningDehydrationAirflowMoistureWater contentHumidityChemistryComposite materialElectrodeMeteorologyThermodynamicsFood science

Abstract

fetched live from OpenAlex

Electrohydrodynamic (EHD) drying is novel nonthermal technology exploiting high-voltage corona discharge for dehydration of heat-sensitive biomaterials. In this study, we investigated the effects of voltage, electrode geometry, air flow, humidity, and material thickness on drying rate of sliced white champignons. In most cases, drying rate of mushrooms was proportional to moisture content, which corresponds to diffusion-limited drying. Decrease of air relative humidity from 70 to 30% or introducing forced air flow 1.0 m/s significantly improved efficiency of EHD drying. Increase of emitters’ density or thickness of mushroom slices negatively influenced drying rate. Effect of EHD on color was insignificant in contrast to forced air drying, which provoked significant browning. Energy, used in EHD drying, was negligibly small as compared to thermal drying. These results have been taken into consideration for up-scaling of the EHD drying.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.005
GPT teacher head0.258
Teacher spread0.252 · 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