Inexpensive Video Drop-camera for Surveying Sensitive Benthic Habitats: Applications from Glass Sponge (Hexactinellida) Reefs in Howe Sound, British Columbia
Bibliographic record
Abstract
Where marine waters are shallow and bathymetric features are steep, the typically employed multi-beam side scan sonar is not always reliable for identifying complex biological structures. Here, we present a cost-efficient method used in Howe Sound, British Columbia, for bathymetric mapping, exploration, and ground-truthing of glass sponge bioherms. A simple depth sounder and software package was used to produce bathymetric maps. From these maps, prospective sites were selected and surveyed to investigate bioherm presence with a simple drop-camera towed off the bow of a small drifting vessel during calm seas. This method was used during a 4-year citizen science initiative that led to the discovery of 12 glass sponge bioherms in Howe Sound, the first step in protecting these globally unique reefs from the impact of bottom-contact fishing, anchoring, and potential industrial contamination. Before our work using this method, only two glass sponge bioherms had been identified in Howe Sound. The method also proved effective as a means to quantify damage to bioherms from fishing gear.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".