Survey of Portable Oil Detection Methods
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
When oil is spilled into the marine environment, it may be found on the water's surface, in the water column, in the sediment, or on the shoreline. When delineating the extent of contamination, it is important to be able to differentiate the spilled oil from other components that may appear to be oil. There are established methods for detecting oil-in-water, such as fluorometry, that allow in situ measurements to be made. In this study, we investigate both established methods and potential technological advancements that could provide a means for a site investigator to gather meaningful on-site information regarding the presence of oil. The primary focus will be usefulness to a shoreline application, but application to other types of samples is addressed. The degree to which an oil could be identified using these portable methods, such as the ability to differentiate petrogenic from biogenic oils, is also discussed. Method comparisons are discussed, with relevance to portability, selectivity, relative cost, and ability to process multiple samples.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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