First tests of hybrid acoustic/archival tags on squid and cuttlefish
Bibliographic record
Abstract
This study demonstrates the simultaneous use of acoustic and archival tags for obtaining data for near-shore species. Australian giant cuttlefish Sepia apama (off Whyalla, South Australia) and the tropical squid Sepioteuthis lessoniana (off Magnetic Island, Queensland, Australia) were tagged using a ‘hybrid’ tag consisting of a Vemco V8 acoustic tag potted with a Vemco minilog temperature–depth archival tag. Four of these animals were released and monitored inside radio-acoustic-positioning-telemetry (RAPT) buoy-system arrays that included bottom-mounted sensors that transmitted independent temperature records and a reference standard for sound conductivity and position. All were subsequently located out of RAPT range and two of the four archival tags were recovered. Tags were located using a boat-mounted hydrophone and VR60 receiver and recovery was aided by a diver operating a hand-held VUR96 receiver. This technology provides a cost-effective alternative to expensive satellite pop-up tags and is suitable for much smaller species that return to near-shore environments.
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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 | 0.000 | 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 | 0.001 |
| 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 teacher head, 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".