Fluorescence excitation–emission matrix (EEM) spectroscopy and cavity ring-down (CRD) absorption spectroscopy of oil-contaminated jet fuel using fiber-optic probes
Bibliographic record
Abstract
Excitation emission matrix (EEM) and cavity ring-down (CRD) spectral signatures have been used to detect and quantitatively assess contamination of jet fuels with aero-turbine lubricating oil. The EEM spectrometer has been fiber-coupled to permit in situ measurements of jet turbine oil contamination of jet fuel. Parallel Factor (PARAFAC) analysis as well as Principal Component Analysis and Regression (PCA/PCR) were used to quantify oil contamination in a range from the limit of detection (10 ppm) to 1000 ppm. Fiber-loop cavity ring-down spectroscopy using a pulsed 355 nm laser was used to quantify the oil contamination in the range of 400 ppm to 100,000 ppm. Both methods in combination therefore permit the detection of oil contamination with a linear dynamic range of about 10,000.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".