Consumer sensory acceptance and value of domestic, Canadian, and Australian grass-fed beef steaks1
Bibliographic record
Abstract
To determine US consumer acceptance and value of beef from various countries, 24 taste panels of consumers (n = 273 consumers) were conducted in Denver and Chicago. Two pairs of strip steaks were evaluated for flavor, juiciness, tenderness, and overall acceptability on eight-point hedonic scales. One pair consisted of an Australian grass-fed strip steak and a domestic strip steak, whereas the other pair included Canadian and domestic strip steaks. The pairs were matched to similar Warner-Bratzler shear values and marbling scores to decrease variation associated with tenderness and juiciness. A variation of the Vickery auction was used to obtain silent, sealed bids on steaks (0.45 kg) from the same strip loins sampled in the taste panel. Consumers gave higher (P < 0.001) scores for flavor, juiciness, tenderness, and overall acceptability for domestic steaks compared with Australian grass-fed steaks. Domestic steaks averaged 3.68/0.45 dollars kg, whereas consumers placed an average value of 2.48/0.45 dollars kg on Australian grass-fed steaks (P < 0.001). Consumers rated Canadian steaks numerically lower for juiciness (P = 0.09) and lower (P < 0.005) for flavor, tenderness, and overall acceptability than domestic samples. Consumers placed an average value of 3.95/0.45 dollars kg for domestic steaks and 3.57/0.45 dollars kg for Canadian steaks (P < 0.01). Consumers (19.0%) who preferred Australian grass-fed steaks over domestic steaks paid 1.38/0.45 dollars kg more (P < 0.001), whereas consumers (29.3%) who favored the Canadian steaks over the domestic steaks paid 1.37/0.45 dollars kg more (P < 0.001) for the Canadian steaks. A majority of US consumers seem to be accustomed to the taste of domestic beef and prefer domestic steaks to beef from Australia grass-fed and Canadian beef.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".