A comparison of two instrumental techniques used to discriminate the cooking quality of spaghetti
Bibliographic record
Abstract
Summary Pasta is a popular food whose quality can be measured by appearance, flavour and texture. Several instruments have been devised to measure texture but there is little comparative information. This study compared the TA.XT2i texture analyser with the viscoelastograph of thirty spaghetti samples. There was a high correlation between these instruments and good agreement in ranks. While both instruments provide comparable data it is not the same. Two laboratories used the texture analyser to measure cooked spaghetti firmness using their own procedures. There was good agreement in firmness, however; there were differences in the ranks for samples that fell between the extremes in firmness. We attributed these differences to variations in the instrument settings, cooking method and sample presentation used by the laboratories indicating the need to standardise the method. Using a standard method greatly improved the correspondence between the laboratories improving the r2 to 0.99 with excellent agreement in the ranking of ten samples.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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 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".