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Record W2051465371 · doi:10.2202/1556-3758.1071

Mass Transfer Characteristics of Chicken Nuggets

2006· article· en· W2051465371 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

VenueInternational Journal of Food Engineering · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Quality and Safety Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsThermal diffusivityMoistureFood scienceChemistryMass transferDeep fryingDiffusionWater contentAnalytical Chemistry (journal)ChromatographyThermodynamicsOrganic chemistry

Abstract

fetched live from OpenAlex

Chicken nuggets were either deep fat fried at three temperatures (150, 170 and 190oC) for 1 to 4 min or oven baked at three temperature levels (200, 220 and 240oC) for 5 to 25 min. The effects of these cooking methods on mass transfer characteristics of chicken nuggets were evaluated. Moisture loss profiles in the breading and core portions of the product were significantly different. There was a rapid moisture loss from the breading portion within the first 2 min of deep fat frying or within the first 15 min of oven baking followed by considerably reduced rates. Moisture loss in the core region changed only slightly in the early stages of frying or oven baking but increased afterwards. Moisture diffusivity in the breading region was evaluated using analytical solution of Fick’s second law diffusion equation. Values of moisture diffusivity were from 20.93x10-10 to 29.32x10-10 m2/s for deep fat frying and from 1.90x10-10 to 3.16x10-10 m2/s for oven baking. The activation energies were 8.04 and 25.7 kJ/mol for deep fat frying and oven baking, respectively.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.877
Threshold uncertainty score0.116

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 head0.011
GPT teacher head0.193
Teacher spread0.182 · 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