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Record W2946888557 · doi:10.1111/jtxs.12448

The influence of batter formulation and predrying time on interparticle space fractions of a coated meat analog

2019· article· en· W2946888557 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 Texture Studies · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsSte. Anne's HospitalMcGill UniversityAgriculture and Agri-Food Canada
Fundersnot available
KeywordsFood scienceMoistureMaterials scienceMathematicsPorosityWater contentChemistryComposite materialEngineering

Abstract

fetched live from OpenAlex

The purpose of the study was to understand the mechanism of microstructural changes in vegetable-based meat analogs coated with different batter formulations. A meat analog (substrate) was developed by using vegetable proteins, coated with batters formulated from different combinations of wheat and rice flours, predried at various durations, and subsequently fried. The effect of batter formulation, predrying time, and frying time on spaces occupied by air (porosity, SOA), moisture (SOM), and fat (SOF) in the core region (the meat analog) was studied. The SOA, SOM, and SOF ranged between 8.28-32.72%, 16.73-58.31%, and 16.73-58.31%, respectively. All three fractions of pores in the meat analog were significantly influenced by predrying and frying times; however, batter formulation did not show any significant influence. Batter formulation did not show any significant influence on moisture and fat content within the meat analog. Fat content was not influenced by frying time; and only 90 min predrying made a difference.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score0.062

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 head0.029
GPT teacher head0.286
Teacher spread0.258 · 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