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Record W2147093999 · doi:10.1177/1082013208100534

Microwave and Radio Frequency Heating

2008· article· en· W2147093999 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

VenueFood Science and Technology International · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Inactivation Methods
Canadian institutionsMcGill University
Fundersnot available
KeywordsDielectric heatingMicrowaveMaterials scienceRadio frequencyProcess engineeringSterilization (economics)ThermalOverheating (electricity)Nuclear engineeringOptoelectronicsEnvironmental scienceDielectricElectrical engineeringTelecommunicationsComputer scienceEngineering

Abstract

fetched live from OpenAlex

This paper brings to perspective issues related to research initiatives for the application of microwave (MW) and radiofrequency (RF) applications in foods. Both MW (300 MHz and 300 GHz) and RF waves (3 kHz — 300 MHz) are part of the electromagnetic spectrum that result in heating of dielectric materials by induced molecular vibration as a result of dipole rotation or ionic polarization. They have been credited with volumetric heat generation resulting in rapid heating of foodstuffs. Due to their lower frequency levels, RF waves have a larger penetration depth than MW and hence could find better application in larger size foods. Besides the popular domestic use of MW ovens, commercialized applications of MW/RF heating include blanching, tempering, pasteurization, sterilization, drying, rapid extraction, enhanced reaction kinetics, selective heating, disinfestations, etc. This paper reviews the current status and research needs for in-packaged sterilization technologies for commercial applications. Technological challenges include process equipment design, microbial destruction and enzyme inactivation kinetics, temperature and process monitoring, and achieving of temperature uniformity. Other issues also relate to the use of packaging material in in-package sterilization applications, package/container concerns in domestic MW ovens, receptor technology for creating dry-oven conditions, modeling and time-temperature process integrators. There is also the issue of non-thermal and enhanced thermal effects of microwave heating on destruction kinetics.

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 score0.016
Threshold uncertainty score0.320

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 studies0.0000.001
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 head0.017
GPT teacher head0.278
Teacher spread0.261 · 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