Beached Bird Surveys and Chronic Oil Pollution in Central California
Bibliographic record
Abstract
This report summarises beached bird and oil pollution data gathered from September 1993 through August 2002 by Beach Watch, a longterm shoreline monitoring program.Surveys were conducted at 32 beach segments ranging from southern San Mateo County to southern Sonoma County.Beached birds were most commonly found in August and September, and most birds at this time were local nesting marine species.During the 1997/98 El Nio-Southern Oscillation (ENSO) event, the annual encounter rate for all beached birds more than doubled, and the encounter rate for oiled birds increased more than six-fold.Also during the 1997/98 ENSO the encounter rate for tarballs (hardened patties of oil) was more than twenty times that observed for the preceding year.Periodic increases of oiled birds and tarballs may have reflected the corresponding releases of heavy fuel oil from long submerged vessels, such as the SS Jacob Luckenbach, as well as illegal discharges from merchant and tank vessels.The percentage of beached birds found oiled was lower than that reported in the southern North Sea (1977-1997) and in Newfoundland (1984-1999).Comparison with an earlier beached bird dataset from central California from 1971 to 1981(Stenzel et al. 1988) suggests that oiling rates have declined since that decade.The observations recorded by Beach Watch have contributed to the discovery, identification and prosecution of sources of pollution.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".