MétaCan
Menu
Back to cohort
Record W2805939746 · doi:10.1139/cjas-2017-0217

Amino acid digestibility in six sources of meat and bone meal, blood meal, and soybean meal fed to growing pigs

2018· article· en· W2805939746 on OpenAlexvenueno aff
D. M. D. L. Navarro, John Mathai, Neil Jaworski, Hans H Stein

Bibliographic record

VenueCanadian Journal of Animal Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsMeat and bone mealMealSoybean mealLatin squareBlood mealLysineFood scienceFish mealBone mealAnimal scienceChemistryAmino acidBiologyBiochemistryRumenFermentation

Abstract

fetched live from OpenAlex

Standardized ileal digestibility (SID) of amino acids (AAs) by growing pigs was determined in blood meal and six sources of meat and bone meal (MBM). Eighteen ileal-cannulated barrows (initial body weight: 69.3 ± 4.4 kg) were randomly allotted to a replicated 4 × 9 incomplete Latin square design with four periods and nine diets, giving eight replications per diet. One diet included 33% soybean meal (SBM) as the sole source of AA. Seven diets contained 9% blood meal or 9% of one of the six sources of MBM and 22% SBM as the only AA containing ingredients. The last diet was a nitrogen (N) free diet. Results indicated that the SID of all AAs were different (P < 0.05) among the six sources of MBM, but the SID of lysine (Lys) could not be predicted from the ratio between Lys and crude protein. For some, but not all AAs, the average SID in MBM was greater (P < 0.05) than in blood meal, but for most AAs the SID in MBM was less (P < 0.05) than in SBM. It is concluded that, as is the case for most other co-products, differences in concentration and SID of AAs among sources of MBM exist.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.024
GPT teacher head0.232
Teacher spread0.208 · 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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Animal ScienceSame topicAnimal Nutrition and PhysiologyFrench-language works237,207