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Record W2024220949 · doi:10.2527/af.2013-0014

Swine convert co-products from food and biofuel industries into animal protein for food

2013· article· en· W2024220949 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

VenueAnimal Frontiers · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsAgriculture Food and Rural DevelopmentUniversity of Alberta
Fundersnot available
KeywordsAnimal feedSoybean mealBiofuelFood scienceFood processingAnimal foodBiotechnologyMealProduction (economics)BusinessBiologyRaw material

Abstract

fetched live from OpenAlex

As omnivores, pigs are ideally suited to convert non human-edible feedstuffs into high quality food animal protein. Dietary inclusion of co-products from food and bio-fuel production will considerably improve the human-edible protein balance (edible protein output/input) of swine production. Compared with traditional diets based on a single grain as an energy source and soybean meal as a protein source, feeding high inclusion levels of co-products has a greater risk. This risk can be managed using modern feed formulation, feed evaluation, feed enzymes, and feed processing to attain predictable swine growth performance, carcass characteristics, and pork quality. Dietary inclusion of co-products reduces feed cost per unit of pork produced and is part of an effort to create sustainable swine production systems. Fast adoption of feeding co-products is driven by unprecedented high corn and soybean meal prices.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.772
Threshold uncertainty score0.377

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 head0.023
GPT teacher head0.211
Teacher spread0.188 · 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