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Record W1891121146 · doi:10.2527/2000.7851267x

Riboflavin and niacin concentrations of bison cuts.

2000· article· en· W1891121146 on OpenAlexaboutno aff
J.A. Driskell, M. J. Marchello, D.W. Giraud

Bibliographic record

VenueJournal of Animal Science · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsnot available
Fundersnot available
KeywordsNiacinRiboflavinAnimal scienceThiamineFood scienceMediusHayLongissimus dorsiChemistryBiologyBiochemistryAnatomy

Abstract

fetched live from OpenAlex

We analyzed the riboflavin and niacin contents of individual cuts from clod (triceps brachii), ribeye (longissimus thoracis), top round (semimembranosus), and top sirloin (gluteus medius) from 24 fed bison bulls. The bulls came from producers in the United States and Canada and had consumed concentrate diets plus hay free choice for at least 100 d. The mean riboflavin and niacin concentrations of all of the bison cuts combined were .094 and 1.910 mg/100 g wet weight, respectively. The riboflavin and niacin content values did not differ (P < .05) among the cuts of meat. Cuts from individual bulls were significantly different (P < .05) with regard to both riboflavin and niacin contents. Little variation was observed in riboflavin and niacin content of five bison from the same producer and two bison from another producer. These content values may be used in estimating the riboflavin and niacin content of bison meat.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.278
Teacher spread0.242 · 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 designBench or experimental
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

Citations12
Published2000
Admission routes1
Has abstractyes

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