MétaCan
Menu
Back to cohort
Record W4414651844 · doi:10.14738/aivp.1305.19378

Reviewing the Control of Meat pH and Light Scattering in Model Systems

2025· article· en· W4414651844 on OpenAlexaff
H. J. Swatland

Bibliographic record

VenueEuropean journal of applied sciences · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBirefringenceMyofilamentLight scatteringReflectivityMicroscopeOptical microscopeMyofibrilBuffer (optical fiber)Diffraction

Abstract

fetched live from OpenAlex

This review explains how a computer controlled system was developed to perfuse individual meat muscle fibres with phosphate buffer to change their pH. Fibres were mounted on a frame in an optical cell on a polarizing microscope to measure their birefringence. As pH was decreased, birefringence was increased. X-ray diffraction showed that this was caused by thick and thin myofilaments in the fibres moving closer together laterally. Small disks of intact muscle were measured in a macroscopic system to show that a decrease in pH caused an increase in reflectance. When pH was increased, reflectance decreased. These model systems explain how living muscle usually gets brighter as it becomes 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)0.004
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 score0.769
Threshold uncertainty score0.145

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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 head0.050
GPT teacher head0.246
Teacher spread0.196 · 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 designBench or experimental
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueEuropean journal of applied sciencesSame topicMeat and Animal Product QualityFrench-language works237,207