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MODELING AND SIMULATION OF UNFROZEN HAMBURGER SINGLE‐SIDED PANFRYING WITH FLIPPINGS FOR MICROBIAL SAFETY

2006· article· en· W2092646227 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

VenueJournal of Muscle Foods · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicListeria monocytogenes in Food Safety
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMass transferListeria monocytogenesHeat transferFood scienceMoistureBiological systemEnvironmental scienceChemistryMechanicsMaterials scienceBiologyChromatographyBacteriaPhysicsComposite material

Abstract

fetched live from OpenAlex

ABSTRACT The predictive mathematical heat and mass transfer models for the hamburger patty of single‐sided panfrying were developed. The predicted patty‐temperature histories agreed well with the observed temperature histories. Good experimental validations demonstrated that the mass transfer model provided the feasibility of simulating moisture‐ and fat‐loss histories. The safety analysis was conducted to predict the slowest microbial inactivation point within a patty using the microbial inactivation model. The simulation results demonstrated the inactivation of Escherichia coli O157:H7, Listeria innocua and Salmonella serotypes within patties during cooking. The effects of various turning intervals, patty thickness, initial patty temperature and D (thermal death time) values on process time were analyzed.

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 score0.163
Threshold uncertainty score0.428

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 head0.043
GPT teacher head0.286
Teacher spread0.244 · 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