Echolocation signals of foraging killer whales (<i>Orcinus orca</i>)
Bibliographic record
Abstract
Fish eating resident killer whales that frequent the coastal waters of Vancouver Island, Canada have a strong preference for chinook salmon. The whales in Johnston Strait often forage along the steep cliffs that extend into the water, echolocating their prey. Echolocation signals were measured with a four hydrophone symmetrical star array and the signals were simultaneous digitized at a sample rate of 500 kHz using a lunch-box PC. A portable VCR recorded the images from an underwater camera located close to the array center. Only signals emanated from close to the beam axis (1185 total) were chosen for a detailed analysis. Killer whales project very broad band echolocation signals (Q 1.3 to 1.5) that tend to have a bimodal frequency structure. Ninety seven percent of the signals had center frequencies between 45 and 80 kHz with a band-width between 35 and 50 kHz. The peak-to-peak source level of the echolocation signal decreased as a function of the one way transmission loss to the array. Source levels varied between 200 and 225 dB re 1 μPa. Using a model of target strength for chinook salmons, the echo levels from the echolocation signals are estimated for different ranges between whale and salmon.
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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 | 0.000 |
| 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) | 0.002 | 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".