PARTICLE SIZE ANALYSIS OF DISPERSED OIL AND OIL‐MINERAL AGGREGATES WITH AN AUTOMATED ULTRAVIOLET EPI‐FLUORESCENCE MICROSCOPY SYSTEM
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
This paper describes recent advances in microscopic analysis for quantitative measurement of oil droplets. Integration of a microscope with bright-field and ultraviolet epi-fluorescence illumination (excitation wavelengths 340-380 nm; emission wavelengths 400-430 nm) fitted with a computer-controlled motorized stage, a high resolution digital camera, and new image-analysis software, enables automatic acquisition of multiple images and facilitates efficient counting and sizing of oil droplets. Laboratory experiments were conducted with this system to investigate the size distribution of chemically dispersed oil droplets and oil-mineral aggregates in baffled flasks that have been developed for testing chemical dispersant effectiveness. Image acquisition and data processing methods were developed to illustrate the size distribution of chemically dispersed oil droplets, as a function of energy dissipation rate in the baffled flasks, and the time-dependent change of the morphology and size distribution of oil-mineral aggregates. As a quantitative analytical tool, epifluorescence microscopy shows promise for application in research on oil spill response technologies, such as evaluating the effectiveness of chemical dispersant and characterizing the natural interaction between oil and mineral fines and other suspended particulate matters.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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