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Record W3091897704 · doi:10.5539/jfr.v9n6p13

Changes in the Physicochemical Properties of Kashkaval of Pindos Cheese Produced with Different Salting Methods during Ripening

2020· article· en· W3091897704 on OpenAlexvenueno aff
Eleni C. Pappa, Efthymia Kondyli, Loulouda Bosnea, Marios Mataragas

Bibliographic record

VenueJournal of Food Research · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsnot available
FundersEuropean Regional Development FundEuropean Commission
KeywordsSaltingBrineRipeningFood scienceOrganolepticChemistryCheese ripeningMozzarella cheeseOrganic chemistry

Abstract

fetched live from OpenAlex

Kashkaval of Pindos cheeses were produced either with sheep (100%) or mixture of sheep (90%) - goat (10%) milk. Sheep milk cheeses were manufactured either by dry salting or by immersion in 18% w/w salt (NaCl) brine. Cheeses made with the mixture of sheep- goat milk were directly immersed in brine of 15% or 18% w/w NaCl concentration. These are common practices of cheese salting used by the traditional cheese-makers. The physicochemical characteristics of all cheeses were monitored during a ripening period of 3-months. The results have shown that the physicochemical characteristics of both cheeses were not affected by the different salting methods. Therefore, Kashkaval of Pindos cheese can be salted either with dry salt or with immersion in brine, without altering their main composition and organoleptic characteristics. Furthermore, some historical data about Kashkaval of Pindos cheese are included.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.173
GPT teacher head0.346
Teacher spread0.173 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2020
Admission routes1
Has abstractyes

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