Killer Whale Foraging Drone Observations - Coastal British Columbia - 2019 & 2020
Bibliographic record
Abstract
The Hakai Institute's contribution to the project was to record feeding, social interactions, and provide imagery for identifying and determining the size of the killer whales being studied. The killer whale study was conducted with the partnership of University of British Columbia's Marine Mammal Research Unit. UBC project leads were Sarah Fortune and Andrew Trites. Permit Information: DFO and UBC animal care permit info (XMMS 6 2019 & A19-0053) Results and full methodology documentation to be completed after the 2019 & 2020 field seasons. Research occurred aboard two vessels - the M/V Gikumi (18 m wooden, liveaboard vessel) and the Steller Quest (6 m aluminium hull vessel). The M/V Gikumi was used to collect hydroacoustic data, survey for marine mammals, conduct focal follows and facilitate drone operations. The Steller Quest was principally used for the deployment of suction-cup attached Customizable Animal Tracking Solutions tags (CATs tags) and tracking tagged animals. An overview map (Fig. 1) details the route and areas of concentrated research activity. The main research goal was to collect comparative information about the feeding behaviour of Southern and Northern resident killer whales and the vertical distribution and abundance of their prey (e.g., Chinook salmon). Datasets: 4k video, GPS track data, flight laser altimeter data. Processed killer whale data are under review. Overview of the research themes: Focal follows Visual observation of animals were made from the vessel to continuously record their location and behaviour concurrent with the collection of physical oceanographic data (salinity and temperature) and prey data. Hydroacoustics Multi-frequency echosounders were used to collect fine-scale information about the vertical distribution and abundance of encountered prey (e.g., Chinook, Sockeye, Coho). These data will be used to quantitatively assess the quality and quantity of prey in Northern and Southern resident killer whale habitat. Biologgers To record underwater dive patterns and feeding behaviour at depth using a biologer with a high-definition video camera, time-depth recorder, accelerometer and magnetometer, fast acquisition GPS and hydrophone. The tag will be used to kinematically and acoustically determine when and where whales capture their prey and how successful they are at hunting. Drone imagery To record feeding, social interactions, and provide imagery for identifying and determining the size of the killer whales being studied.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.005 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.133 |
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; both teacher heads agree on what is shown here.
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".