VEGETATION RESPONSE AND SEDIMENT POLYCYCLIC AROMATIC HYDROCARBON ATTENUATION IN A CAREXMARSH IN HOWE SOUND, BRITISH COLUMBIA, CANADA FOLLOWING A SPILL OF BUNKER C Fuel Oil
Bibliographic record
Abstract
ABSTRACT A spill of Bunker C fuel oil in Howe Sound, British Columbia, Canada in August 2006 affected approximately 10.5 acres (4.2 hectares) of marsh habitat unique to the Pacific Northwest. A cleanup approach to reduce impacts from response actions was balanced with a desire to remove all residual oil. Cleanup techniques that were used include flushing, cutting, raking, passive sorbent collection, natural recovery, and manual excavation (sediment removal). Evaluation of the habitat response relative to oiling conditions and treatments was undertaken by examining vegetation indices in treatment and control areas and temporal changes in sediment concentrations of poly cyclic aromatic hydrocarbons (PAHs). One year post-spill results suggest that the amount or degree of oiling on the dominant vegetation, Carex lyngbyei and ?leocharis palustris, had little or no apparent effect, or was insignificant in comparison to the impact of the treatment. Vegetation cutting alone had no positive or negative effect on vegetation recovery indices. Treatments which were aggressive in physically disturbing the sediments and root systems of the marsh (heavy trampling, heavy scraping, excavation and/or excessive trampling) retarded vegetation recovery in oiled and unoiled habitats and prolonged oil persistence in comparison to non aggressive treatment, vegetation cutting alone or natural recovery. Mechanical damage was the best predictor of ?AH persistence.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".