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Comparison of Net Portal Absorption with Predicted Flow of Digestible Amino Acids: Scope for Improving Current Models?

2006· article· en· W2074606373 on OpenAlexafffund
D. Pacheco, C.G. Schwab, R. Berthiaume, G. Raggio, H. Lapierre

Bibliographic record

VenueJournal of Dairy Science · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversité LavalAgriculture and Agri-Food Canada
FundersDairy Farmers of Canada
KeywordsAnimal scienceDilutionStandard errorMathematicsRumenFactorial experimentChemistryStatisticsBiologyFood science

Abstract

fetched live from OpenAlex

This study was undertaken to determine the relationship between measured net portal absorptions (NPA) and flows of digestible essential amino acids (EAA) predicted with the National Research Council model (NRC, 2001) or the Cornell Net Carbohydrate and Protein System model (CNCPS, version 5.0.34). Net portal absorption data were obtained from 33 measurements of portal-arterial plasma EAA concentration differences among 8 treatments in lactating dairy cows, with plasma flow estimated from downstream dilution of para amino-hippurate. The predicted digestible flows from NRC (2001) related better than CNCPS to NPA observed in our studies, as shown by the lower standard errors on the slopes for all EAA and lower root mean prediction errors for all EAA except Met and Phe. However, the partitioning of the prediction error indicated a systematic underprediction (mean bias) for the NRC model (2001), with the exception of Ile. It is important to note that a relationship of unity was not expected, as discussed in the paper, because of losses of EAA through portal-drained viscera metabolism. A revised set of predictive equations for digestible EAA was obtained using a subset of data from NRC (2001) limited to trials conducted with dairy cows. This increased the predicted flows of digestible EAA by only 2%. Flows of digestible EAA were also estimated using a factorial approach, assuming an AA composition for each fraction of the duodenal flow estimated by NRC (undegradable, microbial, and endogenous proteins). This resulted in a slight improvement in the slope of the regression between predicted flows and measured NPA, but still yielded predicted digestive flows that were too low to support observed NPA. Finally, on the basis of literature values, increment of the digestibility of the undegradable fraction of forages and of microbial protein is suggested to improve the relationship between predicted digestible flows and NPA. Overall, this study indirectly confirms, across EAA, smaller losses through gut metabolism for His, Met, and Lys, intermediate losses for the branched-chain AA with the higher losses for Thr.

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)0.017
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.035
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0040.006
Open science0.0040.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.033
GPT teacher head0.276
Teacher spread0.243 · 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 designSimulation or modeling
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

Citations29
Published2006
Admission routes2
Has abstractyes

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