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Textural, Water Holding, and Sensory Properties of Low‐fat Pork Bologna with Normal or Waxy Starch Hull‐less Barley

2000· article· en· W2144171664 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 Food Science · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsFood scienceStarchChemistryBarley flourMoistureWheat flourWater activityWaxy cornComposition (language)Water content

Abstract

fetched live from OpenAlex

ABSTRACT: All ultra‐low‐fat (< 1%) pork bolognas had similar cook yield and composition. Addition of 4% hull‐less waxy barley flour or meal to formulations provided the greatest purge control; 4% normal starch barley, wheat flour and potato starch were intermediate; 0.25% kappa‐carrageenan or 1% soy protein concentrate had little effect on water holding and texture. Expressible moisture and purge were significantly correlated to moisture content and batter viscosity. Formulations with wheat flour and waxy barley meal were scored the firmest, while bologna with potato starch required the most force to compress. For most sensory properties, barley fractions performed similarly to wheat flour; however, waxy barley provided superior water holding during storage.

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)0.001
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 score0.055
Threshold uncertainty score0.322

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.064
GPT teacher head0.243
Teacher spread0.179 · 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