Organoleptic evaluation of a diabetic-specific oral nutritional supplement with extra virgin olive oil in patients at nutritional risk and type 2 diabetes mellitus: Double-blind, randomized, crossover and multicenter clinical trial (DIACARE)
Bibliographic record
Abstract
Introduction: Introduction: oral nutritional supplements specific for diabetes (DSF) usually have a composition that favors their palatability and simultaneous glycemic and metabolic control. Objetive: to compare the sensory acceptability of a DSF with respect to a standard oral nutritional supplement (STF) in patients at risk of malnutrition with type 2 diabetes mellitus. Method: randomized, double-blind, crossover, multicenter, controlled, double-blind clinical trial. Odor, taste and perceived texture of a DSF and a STD were evaluated using a scale of 1 to 4. Results: twenty-nine patients were recruited and 58 organoleptic evaluations of the supplements were registered. A better evaluation of DSF was observed with respect to STD, although no statistically significant differences were reached: odor, 0.04 (CI 95 %) -0.49 to 0.56 (p = 0.092); taste, 0.14 (CI 95 %), -0.35 to 0.63 (p = 0.561); texture, 0.14 (CI 95 %), -0.43 to 0.72 (p = 0.619). No differences were found when analyzed by order of randomization, sex, degree of malnutrition, greater or lesser degree of complexity, greater or lesser time of evolution of diabetes, or by being older or younger. Conclusions: the specific nutritional supplement for diabetic patients formulated with extra virgin olive oil, EPA and DHA, a specific mixture of carbohydrates, and fiber, presented an adequate sensory acceptance by malnourished patients with type 2 diabetes mellitus.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".