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Record W4283777171 · doi:10.1016/j.nutres.2022.06.009

Contribution of beef to key nutrient intakes in American adults: an updated analysis with NHANES 2011-2018

2022· article· en· W4283777171 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

VenueNutrition Research · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsImpact
Fundersnot available
KeywordsNiacinNutrientBeef cattleDietary Reference IntakeAnimal scienceFood scienceVitaminNational Health and Nutrition Examination SurveyVitamin B12Reference Daily IntakeMicronutrientVitamin EMedicineChemistryBiologyEnvironmental healthPopulationInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

(8.3%), iron (7.6%), phosphorus (6.8%), potassium (5.6%), and magnesium (3%). Lean fresh beef contributed most to the daily intakes of energy and nutrients followed by ground and processed beef. Beef intake also contributed to daily intakes of fat (8.7%), saturated fat (11%), and sodium (2.9%) and lean fresh beef contributed less intakes of fat and saturated fat than ground and processed beef. Beef and particularly lean fresh beef were efficient sources of nutrients and provided more nutrients per 100 kcal than the total diet. In conclusion, based on nutrient contribution, these findings provide evidence to support inclusion of beef (especially lean fresh beef) in dietary recommendations.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.294
Teacher spread0.281 · 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