Distance from shore as an indicator of disturbance of gray whales during a seismic survey off Sakhalin Island, Russia
Bibliographic record
Abstract
A seismic survey was conducted adjacent to the nearshore feeding ground of gray whales Eschrichtius robustus off northeastern Sakhalin Island, Russia. Scan surveys were conducted at 7 shore stations before, during and after the seismic survey. We investigated whether gray whales shifted their distribution with respect to distance from the shoreline in response to acoustic pulses from the seismic source. To do this, we used linear mixed effects modelling that included effects of detection, space and time. Data were tested for effects of magnitude and presence/absence of sound from seismic activity on whale distance from shore. Sound covariates were estimated over 3 temporal scales (8 h, 3 d and since the start of seismic activity) at locations 500 and 5000 m offshore each observation station. Sighting distance from shore was less in poor visibility and at earlier times of day. No significant effects of sound were identified, although data suggest that at most stations, sighting distance from shore increased slightly over the 2 wk of the seismic survey. The analysis was limited, however, by several factors that included low numbers of sightings throughout most of the study, non-availability of data on biomass of gray whale prey and sources of error that could not be accounted for in the model. Sensitivity to potential errors in sighting distance estimation was assessed using a correction factor based on known locations of vessels and gray whales when sighted. The model was refitted using distance-corrected sightings. Results were consistent with the original model.
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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 | 0.000 | 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) | 0.001 | 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".