Athabasca Oil Sands Process Water: Characterization by Atmospheric Pressure Photoionization and Electrospray Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry
Bibliographic record
Abstract
The Athabasca oil sands in Canada are a less conventional source of oil which have seen rapid development. There are concerns about the environmental impact, with particular respect to components in oil sands process water which may enter the aquatic ecosystem. Naphthenic acids have been previously targeted for study, due to their implications in toxicity toward aquatic wildlife, but it is believed that other components, too, contribute toward the potential toxicity of the oil sands process water. When mass spectrometry is used, it is necessary to use instrumentation with a high resolving power and mass accuracy when studying complex mixtures, but the technique has previously been hindered by the range of compounds that have been accessible via common ionization techniques, such as electrospray ionization. The research described here applied Fourier transform ion cyclotron resonance mass spectrometry in conjunction with electrospray ionization and atmospheric pressure photoionization, in both positive-ion and negative-ion modes, to the characterization of oil sands process water for the first time. The results highlight the need for broader characterization when investigating toxic components within oil sands process water.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".