Mapping the penetration and retention potential of two weathered diluted bitumen crude oils for the shorelines of Northern British Columbia, Canada
Bibliographic record
Abstract
With the increase in bitumen production from Alberta's oil sands, there is a related increase in the transport of non-conventional crude oil throughout Canada including proposed pipeline projects to move diluted bitumen (dilbit) to facilities on the East and West coast of Canada. While the behaviour of conventional oil is well known, little information is available about the fate of any potential dilbit spills on marine shorelines. As a part of Enhancing Marine Safety Strategy launched in 2013 by the Government of Canada, a R&D program has been developed by the Emergencies Sciences and Technology Section (ESTS) from Environment and Climate Change Canada (ECCC) to study the behaviour of non-conventional oil. More precisely, one of the objectives is to develop tools to help oil spill responders to predict the fate of dilbit on shorelines of Northern British Columbia (BC). To address this objective, we collected data from three sources; BC segmentation of the upper intertidal zone for the Douglas Channel and Haida Gwaii Island, particle size analysis results of sediment samples collected directly from Northern BC shoreline and meso-scale laboratory research results on the penetration and retention of dilbit in different type of sediment. This last experiment was conducted in laboratory by the contractor Coastal and Ocean Resources Inc. to estimate penetration (cm) and retention (% of the loading) of different weather dilbit (AWB [18% loss by weights] and CLB [15% loss by weight]) in different types of sediments (from coarse sand to very large pebble). These previous data were combined to associate each shoreline type with dilbit penetration and retention data. For each shoreline type, we did a quantitative (penetration) and qualitative (retention) estimation of dilbit properties. The estimations were also visually represented on ArcMap 9.1. In Northern British Columbia, most of the shoreline is associated with low penetration and low retention corresponding to bedrock substrate. Conversely, high penetration and retention is mainly associated with coarse sediments like pebble/cobble beaches. These shoreline types represent an indicator of difficulty of cleanup operations. Likewise, high retention can be found in coarse sediments but also in sensitive shorelines like marshes. So these maps can be used as an operational tool to establish the priorities and to determine the best strategy for the shoreline cleanup methods (penetration maps), but also as an indicator of shoreline sensitivity (retention maps).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".