Preliminary fingerprinting of Athabasca oil sands polar organics in environmental samples using electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry
Bibliographic record
Abstract
There is a growing need to develop analytical methods that can distinguish compounds found within industrially derived oil sands process water (OSPW) from those derived from natural weathering of oil sands deposits. This is a difficult challenge as possible leakage beyond tailings pond containments will probably be in the form of mixtures of water-soluble organics that may be similar to those leaching naturally into aquatic environments. We have evaluated the potential of negative ion electrospray ionization high-resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICRMS) for comparing oil sands polar organics from tailing ponds, interceptor wells, groundwater, river and lake surface waters. Principal component analysis was performed for all species observed. which included the O(2) class (often assumed to be monocarbxoylic naphthenic acids) along with a wide range of other species including humic substances in the river and lake samples: O(n) where n=1-16; NO(n) and N(2)O(n) where n=1-13; and O(n)S and O(n)S(2) where n=1-10 and 1-8, respectively. A broad range of species was investigated because classical naphthenic acids can be a small fraction of the 'organics' detected in the polar fraction of OSPW, river water and groundwater. Aquatic toxicity and environmental chemistry are attributed to the total organics (not only the classical naphthenic acids). The distributions of the oil sands polar organics, particularly the sulfur-containing species, O(n)S and O(n)S(2), may have potential for distinguishing sources of OSPW. The ratios of species containing O(n) along with nitrogen-containing species: NO(n), and N(2)O(n), were useful for differentiating organic components derived from OSPW from those found in river and lake waters. Further application of the FTICRMS technique for a diverse range of OSPW of varying ages and composition, as well as the surrounding groundwater wells, may be critical in assessing whether leakage from industrial sources to natural waters is occurring.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".