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Record W2060901349 · doi:10.1002/agr.20255

Do U.S. food processors respond to sweetener‐related health information?

2010· article· en· W2060901349 on OpenAlexafffund
Getu Hailu, John Cranfield, Rawlin Thangaraj

Bibliographic record

VenueAgribusiness · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomics of Agriculture and Food Markets
Canadian institutionsCargill (Canada)University of Guelph
FundersAgriculture and Agri-Food Canada
KeywordsEconLitCaneEconomicsFood scienceAgricultural scienceAgricultural economicsBusinessBiotechnologySugarChemistryMEDLINEPolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract This study examines the differential effects of relative prices and sweetener‐related health information on the substitutability between sweeteners in the U.S. food processing sector. Results suggest that cane and corn sugar are gross complements, Allen complements, but Morishima substitutes. Furthermore, the Morishima elasticity of substitution (MES) is more responsive to changes in relative prices than to changes in health information. In addition, the MES for cane‐ and corn‐based sweeteners is more responsive to health information from popular media sources than scientific and medical publications. [EconLit citations: D240, I180, Q110]. © 2010 Wiley Periodicals, Inc.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.858
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.011
GPT teacher head0.203
Teacher spread0.192 · 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.

Study designTheoretical or conceptual
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

Citations3
Published2010
Admission routes2
Has abstractyes

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