Experimental Support for a New Drift Block Design to Assess Seabird Mortality from Oil Pollution
Bibliographic record
Abstract
Abstract Seabird mortality from large oil spills and chronic oil pollution is often significant. Total mortality estimates are derived from counts of dead birds that wash ashore and are corrected for numbers lost at sea. Past attempts to estimate proportion of birds that die at sea and wash ashore have included several experiments using carcasses and different types of wooden drift blocks. Results varied greatly depending on environmental conditions and distance from shore where blocks or carcasses were released. Wind seemed to be the predominant factor determining movement over large distances, whereas tidal currents influenced deposition on specific beaches. Determining timing and location of arrival of dead birds on beaches are crucial for accurate mortality estimates. Drift experiments using beached birds that have already drifted at sea for an undetermined length of time are inaccurate due to natural buoyancy loss and decomposition. To determine accuracy of drift block designs used in the past, we compared drift characteristics and patterns between four drift block designs and fresh murre (Uria spp.) carcasses. Our experiments showed that drift blocks used in the past have none of the drift characteristics of dead seabirds, because they have much larger areas exposed to wind and hence drift much faster and farther than murre carcasses. Past mortality estimates using those blocks are therefore doubtful. The drift block design that most accurately mimicked murre carcass drift during our experiments was a 9 × 9 × 14.5 cm wooden block with a 450 gram steel weight that adjusts buoyancy and area exposed to the wind. We propose that in areas where murres are predominant victims of oil spills, that block design be used for all future estimates of oiled seabird mortality.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".