Fluorescence based passive samplers for diluted bitumen in water
Bibliographic record
Abstract
Passive samplers are low-cost and simple devices that can be used to monitor analytes in dynamic systems. In this project, Polydimethylsiloxane and UltraEverDry films were tested for \napplication as passive samplers for dilbit. Three types of oil were used, dissolved, mechanically dispersed, and mechanically dispersed with chemical enhancement. PDMS absorbed oil, with dispersed oil allowing for faster uptake into PDMS than dissolved oil. Equilibration times ranged from 4-8 days for dispersed oil, depending on the thickness of the film. The lower detection limit of the thick PDMS films is approximately 0.4 ppm but can be improved by improving film reproducibility. Thin films had a partition coefficient of approximately 1000 while thick films had a partition coefficient of apprxoximately 6000. Oil can be extracted from PDMS films with ethanol giving a volume dependent signal. Films and ethanol extracts can be used to monitor the concentration of dilbit present in model systems for riverbeds and real-life oil release scenarios. Oil was not observed adsorbed to UltraEverDry.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".