A Comparative Analysis of Creatine, Creatinine, Amino Acid Concentrations and Indispensable Amino Acid Scores of Grain‐Free and Grain‐Inclusive Commercial Extruded Adult Cat Foods
Bibliographic record
Abstract
Despite its role in energy and amino acid (AA) metabolism, no work has investigated creatine (Cr) content in commercial cat food. This study evaluated the Cr, creatinine (CrN), crude protein (CP) and AA concentrations of 30 commercial extruded cat diets. Further, the AA and CP concentrations were used to determine the indispensable amino acid scores (AAS) of the same diets. Diets were classified as grain-free (GF; n = 15) or grain-based (GB; n = 15), then analysed for Cr, CrN, and AA using high-performance liquid chromatography and CP using a nitrogen analyser. Dietary AA and CP concentrations were used to calculate the AAS of each diet, using the recommended allowance for AA requirements from the National Research Council (NRC 2006) and recommendations from the Association of American Feed Control Officials (AAFCO 2023) as reference patterns. Differences in Cr and CrN contents were analysed using PROC GLIMMIX in SAS. The GF diet category exhibited greater (p < 0.05) concentrations of Cr and CrN compared to GB. The most prevalent limiting AA were aromatic AA (AAA) (59%), followed by sulfur AA (SAA) (30%). These findings provide insight into the Cr content in extruded diets, prompting further investigation into the optimal Cr intake required to support AA and energy metabolism in cats.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".