Bibliographic record
Abstract
The aim of the Sources Project is to quantify the environmental risks associated with the large extractive Athabasca oil sands industry, including the development of methods to apportion emissions to their original source. To accomplish either of these tasks for waterborne emissions requires knowing two principle characteristics: the flux (amount) of the emissions and the reactions those emissions undergo within the receiving environment. A Reactive Transport Model (RTM) defines both of these through coupled hydrologic and geochemical models. An RTM is under development for a wetland test site that is down hydraulic gradient from a large, long?lived oil sands tailings pond (TP). Waterborne emissions enter the test site from the western edge and then flow southward along a preferred conglomeratic subsurface conduit. From the conduit emissions spread both laterally and rise to the surface then spread laterally into wetland surface environments. The identification and apportionment of these emissions indicates that multiple metals and isotopic signatures identify the extent of the emissions. However, chloride is the traditional ion used to identify emissions in oil sands monitoring, but it fails to distinguish emissions sources in the test area due to the plethora of potential saline inputs. The geochemical model indicates metal constituents undergo sorption and attenuation along the flow path, with organometallic complexes playing an important but previously unrecognized role. Fluxes will be calculated once the hydraulic model has completed numerical verification. The organic constituents within emissions, primarily napthanic acids (NAs), are commonly regarded as posing the greatest environmental risk from waterborne emissions. However, defining their geochemical behaviour in environmental systems remains problematic. To address this issue an experiment was performed to see if biodegradation was attenuating NAs. Biotraps were installed with an isotopically labelled adamantine structured NA. Extracted phospholipids from the microbes that populated the biotraps demonstrated strong evidence for methanotrophic metabolic pathways, with no evidence the microbiome were biodegrading the NA. This suggests that these adamantine-structured Nas would persist within the Athabasca environment.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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".