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Record W2085429705 · doi:10.1016/j.meatsci.2014.06.024

Red meats: Time for a paradigm shift in dietary advice

2014· article· en· W2085429705 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMeat Science · 2014
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsSystems, Applications & Products in Data Processing (Canada)BIO (Canada)Canadian Council on Animal Care
Fundersnot available
KeywordsRed meatFood scienceNutrientObesityEnvironmental healthMedicineBiology

Abstract

fetched live from OpenAlex

Recent evidence suggests dietary advice to limit red meat is unnecessarily restrictive and may have unintended health consequences. As nutrient-rich high quality protein foods, red meats can play an important role in helping people meet their essential nutrient needs. Yet dietary advice to limit red meat remains standard in many developed countries, even though red meat intakes appear to be within current guidelines. Meanwhile, energy intakes from processed foods have increased dramatically at the expense of nutrient-rich foods, such as red meat. Research suggests these food trends are associated with the growing burden of obesity and associated diseases in recent decades. It is time for dietary advice that emphasizes the value of unprocessed red meat as part of a healthy balanced diet.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score0.220

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)0.0000.000

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 head0.022
GPT teacher head0.286
Teacher spread0.265 · 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