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Food Science Challenge: Translating the Dietary Guidelines for Americans to Bring About Real Behavior Change

2011· article· en· W2125042260 on OpenAlexaff
Sylvia Rowe, Nick Alexander, Nelson G. Almeida, Richard E. Black, Robbie Burns, Laina Bush, Patricia B. Crawford, Nancy L. Keim, Penny M. Kris‐Etherton, Connie M. Weaver

Bibliographic record

VenueJournal of Food Science · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsKellogg's (Canada)SR Research (Canada)
Fundersnot available
KeywordsMandateWork (physics)Food supplyPublic relationsPublic healthMarketingPerspective (graphical)BusinessPolitical scienceMedicineEngineeringEconomicsComputer scienceAgricultural economics

Abstract

fetched live from OpenAlex

Food scientists and nutrition scientists (dietitians and nutrition communicators) are tasked with creating strategies to more closely align the American food supply and the public's diet with the Dietary Guidelines for Americans (DGA). This paper is the result of 2 expert dialogues to address this mandate, which were held in Chicago, Illinois, and Washington, D.C., in early October 2010 between these 2 key scientific audiences. It is an objective that has largely eluded public health experts over the past several decades. This document takes the perspective of food scientists who are tasked with making positive modifications to the food supply, both in innovating and reformulating food products, to respond to both the DGA recommendations, and to consumer desires, needs, and choices. The paper is one of two to emerge from those October 2010 discussions; the other article focuses on the work of dietitians and nutrition communicators in effecting positive dietary change.

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 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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.905
Threshold uncertainty score0.743

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.002
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 head0.181
GPT teacher head0.348
Teacher spread0.167 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations50
Published2011
Admission routes1
Has abstractyes

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