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Record W4409505541 · doi:10.1021/acs.cgd.5c00269

Chocolate Tempering: A Perspective

2025· review· en· W4409505541 on OpenAlexafffund
Jarvis Stobbs, Saeed M. Ghazani, Alejandro G. Marangoni

Bibliographic record

VenueCrystal Growth & Design · 2025
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicFood Chemistry and Fat Analysis
Canadian institutionsCanadian Light Source (Canada)University of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTemperingPerspective (graphical)Materials scienceChemistryMetallurgyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Tempering is a critical step in chocolate production, ensuring desirable properties such as gloss, snap, and bloom resistance. Traditionally, tempering has been understood through the lens of cocoa butter polymorphism, with a predominant focus on achieving Form V crystals, due to their sharp melting profile and associated macroscopic physical properties. However, this Perspective challenges the notion that Form V alone guarantees high-quality, bloom-resistant chocolate. Recent research suggests that polymorphism is only one aspect of chocolate quality. Multiscale structural analyses-including small-angle X-ray scattering (SAXS), ultrasmall-angle X-ray scattering (USAXS), small-angle neutron scattering (SANS), and microcomputed tomography (μCT)-reveal that nanostructural to microstructural properties are key indicators of bloom susceptibility and can vary significantly, despite identical polymorphic phases. This Perspective proposes that tempering should be viewed as a hierarchical crystallization process, where nucleation rate, structural homogeneity, and microstructural organization play critical roles. A broader approach to tempering assessment-integrating microstructural probes alongside traditional solid-state characterization-may provide deeper insights into chocolate's mechanical stability and long-term bloom resistance. As supply chain fluctuations increasingly impact cocoa butter composition, this multiscale perspective could help manufacturers mitigate quality inconsistencies and adapt to cost-driven formulation changes that may otherwise compromise bloom resistance in tempered chocolate.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.046
GPT teacher head0.279
Teacher spread0.234 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations15
Published2025
Admission routes2
Has abstractyes

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