Sediment Core Paleo-analyses, Oil Sands Region
Bibliographic record
Abstract
Sediment from Lakes Polycyclic aromatic hydrocarbons (PAHs), 47 elements including numerous metals, and visible reflectance spectroscopy or VRS-chla have been determined in sediment core samples collected in 2012, 2013 and 2014 from 16 small (surface area 4-97 ha; maximum depth ~1-5 m deep), hydrologically simple lakes located 30 to 120 km from major oil sands development areas. Canadian Council of Ministers of the Environment (CCME) guidelines are available for 13 of the 53 PAHs reported here. Sediment concentrations did not exceed Canadian Council of Ministers of the Environment (CCME) probable effects levels (PELs), which define the level above which biological adverse effects are expected to occur, for PAHs in any lake. Exceedances of the CCME interim sediment quality guidelines (ISQG) for the protection of aquatic life occurred for 4 PAHs (naphthalene, 2-methyl naphthalene phenanthrene, and benzo(a)pyrene) in 8 lakes. CCME sediment quality guidelines are available for 7 of the 47 elements reported here. Exceedances of the CCME ISQG for metals were found for arsenic in 3 lakes, cadmium in 8 lakes, mercury in 3 lakes and zinc in 9 lakes. Exceedances of the CCME PELs for metals occurred in 2 lakes for arsenic and 1 lake for zinc. Further assessment of the data is ongoing to examine reasons for exceedances as well as spatial and temporal trends of the PACs and elements. Analyses of lake primary productivity, using visible reflectance spectroscopy or VRS-chla as a proxy, show consistently greater productivity (i.e. VRS-chla concentrations) in the top sediment core slices relative to the bottom, regardless of lake morphological and limnological characteristics and landscape position. Potential drivers of these changes are being examined.
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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 | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".