Transmitting species‐interaction data from animal‐borne transceivers through Service Argos using Bluetooth communication
Bibliographic record
Abstract
Summary Interactions between upper trophic‐level predators and their prey remain poorly understood due to their inaccessibility during foraging at sea. This uncertainty has fuelled debate on the impact of predation by species such as the grey seal ( Halichoerus grypus ) on fish stocks. The Vemco Mobile Transceiver (VMT) has provided us with new knowledge on interactions between pinnipeds and fish species. However, the necessity to recover the VMT for data retrieval has limited deployments to locations where confidence in instrument recovery is high, and has thus restricted both species and geographical sampling. To overcome these limitations, a Bluetooth link was integrated into the VMT and GPS satellite‐linked transmitter. The two‐unit design allows data collected by the VMT to be transmitted via Bluetooth to the satellite transmitter, which relays the interaction data to the ARGOS satellite system for retrieval. To evaluate in‐situ performance, units were deployed on two adult female grey seals on Sable Island, NS in October 2012 and recovered during the subsequent breeding season. Data archived by the VMT were compared with data uploaded via ARGOS. The deployment periods were 76–84 days. The total number of valid detections archived was 179. All detections archived by the first unit ( n = 66) were transmitted via ARGOS, while all but two of the 113 archived detections from the second unit were transmitted. Detections recovered from both units were from other VMT‐tagged grey seals ( n = 173) and moored V13 transmitters on Middle Bank, Eastern Scotian Shelf ( n = 6). These preliminary results are proof‐of‐concept that integrated Bluetooth VMTs can be used on a broader variety of marine predators to collect data on species interactions in otherwise inaccessible environments and without the need to recover instruments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| 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 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".