Acoustic hydrophone (icListen) deployed on an Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus) to measure habitat specific noise in the Minas Basin, Nova Scotia
Bibliographic record
Abstract
Electronic tags attached to marine mammals and fish have been developed to sample temperature, pressure (depth), and location. Currently, no tag contains a built in broadband acoustic hydrophone. In this project, as a proof of concept, we attached a full-size high frequency 200 kHz 24-bit smart hydrophone (icListen) to an Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus) in order to measure ambient noise from the Minas Basin, Nova Scotia. The front end of the icListen hydrophone was secured to the Atlantic sturgeon through use of a Velcro strap that went around its abdomen, behind the pectoral fins. A line of dissolving suture thread, which passed through a dorsal scute, secured the back end of the icListen to the fish. A V13P acoustic tag glued to the exterior of the icListen was used to track the bioprobe with a VR100 manual tracking unit. Three galvanic releases built into the design corroded after approximately seven hours and released the icListen from the fish. Syntactic foam allowed the icListen to float vertically at the surface and a Single Position Only Tag (SPOT-100) then transmitted location signals to the ARGOS satellite system to direct researchers attempting to retrieve the icListen. Approximately eight hours of acoustic data was collected by the icListen hydrophone during its deployment. Ambient noise was recorded, including a splash upon release, shrimp snapping, boat engine noise, waves, harbour porpoise clicks, and signals from Vemco acoustic transmitters implanted within other fish. Echolocation clicks from a harbour porpoise (Phocoena phocoena) were recorded by the icListen during two separate interactions, both indicating a possible attempt at communication with an acoustic tag. Ten acoustic transmitters were picked up by the VR100; five from Atlantic sturgeon tagged between 2010 and 2012, and five others from striped bass (Morone saxatilis) tagged in 2012. The VR100 identified the IDs of uniquely coded tags, provided a time and location stamp for detections and recorded pressure (depth) readings from some tags. This study provided proof of concept for the deployment of an icListen hydrophone on a marine bioprobe in order to record ambient acoustic data. Insight into the interactions between marine mammals and acoustically tagged fish was gained, and tag data allowed a rough estimate of untagged Atlantic sturgeon to be calculated for the study site, off Kingsport, Nova Scotia.
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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) | 0.003 | 0.001 |
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".