Bibliographic record
Abstract
Previous studies have been conducted to characterize and compare U.S. beef with beef from other countries; however, a comprehensive nationwide U.S. consumer study comparing USDA Choice and USDA Select beef to Canadian AAA and AA grades has not been conducted. The present study was conducted to compare consumer evaluations of U.S. and Canadian beef. Top loin, strip loins (IMPS 180, n = 338) were collected from numerous beef processing plants across Canada and the U.S. and were shipped to the Gordon W. Davis Texas Tech Meat Science Laboratory. All strip loins were aged 21 days and cut into 2.54 cm thick steaks for consumer sensory evaluation, WBS, and proximate analysis. Steaks were served to consumers (n = 642) in Baltimore, Maryland (n = 214), Phoenix, Arizona (n = 218), and Lubbock, Texas (n = 210). All steaks were cooked to a medium degree of doneness (71°C) on a George Foreman grill (George Foreman model GRP99A). Steaks were trimmed of all exterior fat and connective tissue before being fabricated into 1 cm2 samples. The samples were served to consumers in a cafeteria setting under normal light and room temperature. Consumers were asked to give their opinion considering overall like, tenderness like, juiciness like, flavor like, tenderness rating, juiciness rating, flavor rating and likelihood to buy for the first four samples. Consumers were served a fifth sample that was identified as Canadian beef and were asked to give an opinion of factors that affect purchasing in the store, Canadian quality, Canadian safety and what comments come to mind first when thinking of Canadian beef. Consumers could distinguish between marbling and grade levels of steaks. USDA Choice and Canada AAA were rated significantly better (P<0.05) than USDA Select and Canada AA by consumers for all sensory attributes. LSMEANS analysis of likelihood to buy indicated a significant preference (P < 0.05) to buy strip loin steaks of higher quality. USDA Select and Canada AA were less desirable to consumers. Consumers answered four questions based on the knowledge that the fifth sample was Canadian beef. Consumer responses to the fifth sample indicated most consumers make most choices at the meat counter based on the type of cut (38.2%) followed by the appearance of the meat in the package (25.98%). Canadian beef quality was rated "good" by most consumers’ (41%). Canadian beef safety was rated very good or good by most consumers (39.05% and 38.37%). Results from this nationwide consumer study, showed no significant differences between similar grades of beef (i.e. USDA Choice versus. Canada AAA and USDA Select versus. Canada AA) but consumers indicated a preference for higher quality grade beef.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".