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Record W1502876942 · doi:10.5772/26329

Analytical Methods and Phytochemistry of the Typical Italian Liquor "Limoncello": A Review

2012· review· en· W1502876942 on OpenAlexaboutno aff
Marcello Locatelli, Giuseppe Carlucci, Salvatore Genovese, Francesco Epifano

Bibliographic record

VenueInTech eBooks · 2012
Typereview
Languageen
FieldChemistry
TopicSpectroscopy and Chemometric Analyses
Canadian institutionsnot available
Fundersnot available
KeywordsMediterranean climateMediterranean areaScale (ratio)GeographyAgricultural economicsEconomyEconomicsArchaeologyCartography

Abstract

fetched live from OpenAlex

Following an ancient tradition, limoncello is a homemade liqueur obtained from peels of Sorrento lemons. However nowadays, due to the fact that its production on industrial scale is widespread and the demand on the international market is increasing, virtually all kinds of lemons are used to make this liqueur. Its main distinctive feature is a bright yellow colour. Limoncello is served especially after-dinner as a digestive after having been stored in a refrigerator at 4 °C. It is very popular and commonly consumed in all Italy and many areas of the Mediterranean region but it is also becoming famous in other countries like United States, Canada, Australia, New Zealand, and northern Europe.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.004

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 head0.083
GPT teacher head0.430
Teacher spread0.347 · 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 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

Citations3
Published2012
Admission routes1
Has abstractyes

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