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Skim milk cryoconcentration as affected by the thawing mode: gravitational vs. microwave‐assisted

2011· article· en· W2155799980 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

VenueInternational Journal of Food Science & Technology · 2011
Typearticle
Languageen
FieldEngineering
TopicFreezing and Crystallization Processes
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSkimmed milkMicrowaveFraction (chemistry)PotassiumChemistryDry matterAnimal scienceAnalytical Chemistry (journal)ChromatographyMaterials scienceFood scienceBiologyMetallurgyPhysics

Abstract

fetched live from OpenAlex

Summary In the present study, skim milk was successfully cryoconcentrated up to 43.72 ± 0.69% (w/w) total dry matter after four cryoconcentration cycles. Total proteins were concentrated up to 22.49 ± 0.31% (w/w). It was found that the cryoconcentrated skim milk fraction was rich in potassium ions. The effect of the cryoconcentration cycle and thawing mode on process efficiency was studied. The obtained data showed that the cryoconcentration cycle effect was significant ( P < 0.001). The thawing mode (gravitational and microwave assisted thawing) had no effect on process efficiency. However, the microwave assisted thawing mode was more efficient regarding to the time needed to obtain the desired thawed fraction. To achieve high process efficiency, three cryoconcentration cycles were sufficient since the process efficiency drastically decreased after this cycle. The concentration of the dry mater entrapped in the ice fraction was the highest at the fourth cryoconcentration cycle.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.012
GPT teacher head0.243
Teacher spread0.231 · 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