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Record W2588677751 · doi:10.3390/nu9020156

“Cocoa and Chocolate: Science and Gastronomy”—The Second Annual Workshop of the Research Institute on Nutrition and Food Security (INSA): 9 November 2016

2017· article· en· W2588677751 on OpenAlexfundno aff
Malén Massot‐Cladera, Francisco J. Pérez‐Cano, Rafaël Llorach, Mireia Urpí-Sardà

Bibliographic record

VenueNutrients · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Chemistry and Fat Analysis
Canadian institutionsnot available
FundersAgència de Gestió d'Ajuts Universitaris i de RecercaInstituto de Salud Carlos IIICentro de Investigación Biomédica en Red-Fisiopatología de la Obesidad y NutriciónOstravská Univerzita v OstravěMinisterio de Economía y CompetitividadConselho Nacional de Desenvolvimento Científico e TecnológicoERAB: The European Foundation for Alcohol ResearchConsejo Interinstitucional de Ciencia y TecnologíaChina Scholarship CouncilGeneralitat de CatalunyaMinisterio de Ciencia e InnovaciónMinisterio de Educación, Cultura y DeporteSCIEXFederación Española de Enfermedades RarasMinistério da EducaçãoPublic Health Agency
KeywordsGastronomyFood scienceBiologyGeography

Abstract

fetched live from OpenAlex

The Research Institute on Nutrition and Food Security at the University of Barcelona (INSA-UB) was founded in 2005 by twenty-two research groups from the Faculties of Pharmacy and Food Science; Biology; Chemistry; and Geography and History, as well as other UB-affiliated centers and hospitals [...].

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)0.004
metaresearch head score (Gemma)0.003
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0010.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0110.003

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 head0.037
GPT teacher head0.284
Teacher spread0.247 · 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
GenreOther

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

Citations4
Published2017
Admission routes1
Has abstractyes

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