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Record W1982316455 · doi:10.1093/ps/84.5.789

Effects of regular and modified starches on cooked pale, soft, and exudative; normal; and dry, firm, and dark breast meat batters

2005· article· en· W1982316455 on OpenAlexaff
L Zhang, Shai Barbut

Bibliographic record

VenuePoultry Science · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsFood scienceStarchPotato starchChemistry

Abstract

fetched live from OpenAlex

The effects of potato and tapioca starches (regular and modified) on the texture, yield, and microstructure of pale, soft, and exudative (PSE); normal; and dark, firm, and dry (DFD) chicken breast meats were studied. Cook yield and fracture force were higher in DFD than in normal and PSE meat. All starches significantly improved yield with modified tapioca showing the best results. Light microscopy showed even distribution and gelatinization of large potato starch granules and small tapioca granules. Addition of starches to the normal meat (46 < L* < 53, 5.9 < pH < 6.1) resulted in higher modulus of rigidity (G') values above 60 degrees C. During cooling, this trend continued as all starches provided significantly higher G' values compared with the control; regular and modified potato resulted in higher G' values than the tapioca starches. Overall, starch addition can compensate for part of the meat protein functionality lost in PSE meat.

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.

How this classification was reachedexpand

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.823
Threshold uncertainty score0.378

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 communication0.0000.000
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 head0.020
GPT teacher head0.230
Teacher spread0.210 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations59
Published2005
Admission routes1
Has abstractyes

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