Fishing for the missing: The application of recreational fish finders for underwater body detection in shallow waters
Bibliographic record
Abstract
Early detection of submerged bodies is essential to increase the possibility of recovery. Different water bodies present different challenges, particularly rivers and the ocean, where chances of detection are vastly reduced. Modern recreational fish finders incorporate multiple sonar technologies, including Sidescan sonar, at high-frequency resolutions, similar to commercial units. Recreational units are widely available and usually hull-mounted, allowing them to be utilized on almost any vessel in shallow and difficult to navigate environments. Recreational fish finders are currently an untapped resource which may assist search teams with the early detection and recovery of human remains submerged in shallow water (<20 m). This research investigated the efficacy of a modern recreational fish finder attached to a kayak to detect human proxies and living human volunteers submerged at shallow depths in (1) two indoor freshwater environments and (2) two outdoor environments (a freshwater lake and a nearshore coastal environment). Results demonstrated that recreational fish finders can detect human bodies submerged in both fresh and saltwater contexts at shallow depths within the water column and on the water bottom. Recreational units equipped with Sidescan sonar (800 kHz) provided the necessary resolution for underwater body detection at shallow depths. These sophisticated sensors are currently used by recreational boaters and anglers, and offer the opportunity to increase the eyes in the water not just by search and recovery teams, but by the public itself.
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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 | 0.000 |
| 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) | 0.000 | 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".