The Canadian Oil Spill Shoreline Research Program: Establishing a Baseline Dataset for the Marine Coast of Northern British Columbia
Bibliographic record
Abstract
Abstract 2017-182 The dispersal and weathering processes of crude and fuel oils have been studied for decades and significant scientific information has been published. However, the fate and behaviour of spilled nonconventional crude oil such as diluted bitumen products are less well understood. There is concern that a spill of the oil sands diluted bitumen may come into contact with marine shorelines as it is transported throughout Canada. There is uncertainty related to the fate of spilled diluted bitumen and potential interactions with shorelines. A Shoreline Oil Spill Research and Development Program was undertaken by Environment and Climate Change Canada (ECCC). In 2013, a 3-year study was initiated and focused on the marine shorelines of northern British Columbia (BC). Four field campaigns were conducted along the entire length of coast throughout the Douglas and Granville channels as well as Banks and Haida Gwaii islands. The field campaigns were used as an opportunity to develop and employ a new approach to collect and compile an extensive pre-spill baseline dataset. Data included an aerial survey with high definition video and a ground survey of representative shorelines where samples were collected and analyzed for petroleum hydrocarbons, carboxylic acid, pesticides, heavy metals, calcium carbonate and sediment grain size. Baseline levels of hydrocarbons in the sediment of the study areas were estimated based on the analysis of total petroleum hydrocarbons (TPH), n-alkanes ranging from n-C9 to n-C40, petroleum related biomarkers such as terpanes and steranes, polycyclic aromatic hydrocarbons (PAHs) and their alkylated homologues (APAHs).
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.012 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".