Measuring speed of vessels operating around endangered southern resident killer whales (Orcinus orca) in Salish Sea critical habitat
Bibliographic record
Abstract
Motorized vessels are a major source of anthropogenic noise and can have adverse effects on species relying on sound for communication and feeding. Monitoring noise levels received by endangered southern resident killer whales (SRKWs) requires knowing the number, distance, and speed of surrounding vessels, including small boats that do not have Automatic Identification Systems (AIS). A method for estimating their speed is required to predict received noise levels and compliance with vessel regulations. We compared theodolite and photogrammetry methods to estimate the number, distance, and speed of vessels in SRKW Salish Sea summertime critical habitat. By treating AIS as "truth", we found photogrammetry-derived ranges and speeds were more variable than theodolite estimates. Error in photogrammetry-derived speeds increased with range. Overall, we found time saved in the field using photogrammetry was more than offset by long analysis time. Theodolite data were relatively easy to collect, and produced accurate and precise results.
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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 | 0.001 |
| 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) | 0.001 | 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".