Bibliographic record
Abstract
A follow-up to the successful CORES Project (2009-2014), SOURCES (SOurce apportionment Using isotope Ratio Characterization of oil sands Environmental Samples; 2014-2019) is focused on the development and application of geochemical and isotopic methodologies to distinguish between natural and anthropogenic contaminants and to better understand processes controlling their distribution in Northern Alberta's Athabasca oil sands region. The project is divided into research projects centred on airborne and waterborne contaminants. The airborne component to SOURCES is examining inorganic nitrogen species (NH3/NH4 and NO3) in air, soils and trees, and organic contaminants (polycyclic aromatic hydrocarbons - PAHs) in lake sediments and snow. The waterborne activity is focused on the surface water-groundwater interactions in areas potentially impacted by emissions from the large tailings ponds. The main contaminants of concern for the waterborne component are metals and naphthenic acids - a complex mixture of carboxylic acids found naturally in bitumen that become concentrated in oil sands process-affected water. As of spring 2017, most fieldwork required to support this research (both components) has been carried out. Analyses on PAHs in lake sediments and snow, nitrogen and nutrients in tree rings and soils, and metals and naphthenic acids in groundwater and surface water samples are ongoing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.071 | 0.022 |
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".