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An Ultrasonic Method for Assessing the Residence Time Distribution of Particulate Foods During Ohmic Heating

2000· article· en· W2046928803 on OpenAlexaff
M. Marcotte, Maher Trigui, J. Tatibouët, Hosahalli S. Ramaswamy

Bibliographic record

VenueJournal of Food Science · 2000
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Chemometric Analyses
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsUltrasonic sensorSonicationGravimetric analysisParticulatesResidence time distributionStarchMaterials scienceCopperChemistryAnalytical Chemistry (journal)ChromatographyMineralogyMetallurgyAcousticsFood science

Abstract

fetched live from OpenAlex

ABSTRACT: The residence time distribution (RTD) was investigated using ultrasound during continuous ohmic heating of 1) starch solution and 2) carrot particles/starch solution mixtures. For liquid experiments, a copper pigment was used as a tracer. Ultrasonic sensors were placed at the end of the tube to measure changes in sound attenuation. The copper concentration was determined in samples taken at time intervals. For particulate foods, one kilogram of carrot/solution mixtures was introduced. Results of the ultrasonic method were compared to carrots weights in collected samples. Variations of sound attenuation illustrated well the RTD of solutions and carrot particles. Results of the ultrasonic method agreed with the pigment method for liquid and the gravimetric method for particulate foods.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.309

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0010.000
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 head0.021
GPT teacher head0.359
Teacher spread0.338 · 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 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

Citations13
Published2000
Admission routes1
Has abstractyes

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