A high-throughput plasmonic tongue using an aggregation assay and nonspecific interactions: classification of taste profiles in maple syrup
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A simple colorimetric test detects off-flavour profiles of maple syrups in minutes, which are detectable by the naked eye. As flavour profiles are due to complex mixtures of molecules, the test uses nonspecific interactions for analysing the aggregation and color change of Au nanoparticles (AuNPs) induced by the different organic molecules contained in off-flavour maple syrup. The test was optimal with 13 nm citrate-capped AuNPs reacting 1 : 1 with pure maple syrup diluted 10 times. Under these conditions, normal flavour maple syrups did not react and the solution remained red, while off-flavoured maple syrups aggregated the AuNPs and the solution turned blue. Different classes of molecules were then tested to evaluate the types of compounds typically found in maple syrups reacting in the test, showing that sulfur- and amine-containing amino acids and aromatic amines caused aggregation of the AuNPs. The test was validated with 1818 maple syrup samples from the 2018 harvest in Quebec and 98% of the off-flavoured maple syrups were positively identified against the standard taste test. Preliminary tests were performed on site in maple sugar shacks to validate the applicability of the test on the production site.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 it