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Record W2081499179 · doi:10.1162/leon_a_00243

Cornucopia: The Concept of Digital Gastronomy

2011· article· en· W2081499179 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueLeonardo · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsnot available
FundersUniversity of Illinois at Urbana-ChampaignUniversity of California, Santa BarbaraArizona State UniversityUniversidad de San BuenaventuraUniversidade do MinhoUniversità della CalabriaUniversity of WashingtonConcordia UniversitySan Francisco State UniversityUniversity of DenverUniversity of California, Santa CruzIntel Corporation
KeywordsGastronomyFlexibility (engineering)Computer scienceSpace (punctuation)MultimediaGeographyMathematics

Abstract

fetched live from OpenAlex

The authors present a new concept of digital gastronomy—Cornucopia, a futuristic cooking methodology based on digital technologies. They discuss how they have merged kitchen tools with science fiction and actual technologies to create this new design space for gastronomy. The Virtuoso Mixer, the Digital Fabricator and the Robotic Chef were conceptualized to enable more flexibility and control over each of the most important elements of cooking: mixing ingredients, modeling food shapes and transforming edible matter from one state to another. The authors discuss related work and ideas, present their designs and propose their vision for the emerging design space of digital gastronomy.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 head0.027
GPT teacher head0.190
Teacher spread0.162 · 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