Analytical approaches to characterising fish tainting potential of oil sands process waters
Bibliographic record
Abstract
A three-stage study has been carried out with rainbow trout (Oncorhyncus mykiss) to develop analytical approaches which can provide a fingerprint for tainting by oil sands chemicals from process-affected waters and natural sources. The objective was to find a simpler alternative to sensory evaluation. In the first stage, a set of seven test compounds was added to fish tissue which was analysed by headspace and solvent (dichloromethane, DCM) extraction followed by gas chromatography-mass spectrometry (GC-MS). In the second stage, fingerlings (5-20 g) were exposed for 96 hours to the test compound mixture at 1.0 and 0.5 times the estimated tainting threshold concentrations. In the final stage, fingerlings were exposed for 96 hours to an oil sands process water at 5, 10, 20 and 50% concentrations in clean water. None of the test compounds was identified in DCM extracts of tissue from exposed fish. Two long-chain aldehydes, hexadecanal and 9-octadecenal, were tentatively identified in these extracts by matching of mass spectra with library spectra.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".