Wettability-Based Colorimetric Test Strips for Gasoline/Oil Mixture Differentiation
Bibliographic record
Abstract
As inspired by the pH paper for the determination of the acidity levels of solutions, we have developed a wettability-based colorimetric test strip to differentiate the composition of gasoline/oil mixtures. These mixtures are widely used in two-stroke motor engines. A method that is rapid, low cost and simple-to-use will facilitate the differentiation of these gasoline/oil mixtures, and ensure the use of these mixtures in the proper ratios in two-stroke engines for optimized engine performance and endurance. An inverse opal film (IOF) consisting of nanopores was synthesized on the silicon strips. These strips were then functionalized with alkysilanes through chemical vapor deposition. Based on the observation that the silanized nanopores are wetted or not wetted by the gasoline/oil mixtures, we are able to differentiate between the 16:1 and 1:1 mixtures.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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 | 0.001 |
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".