Detecting Indicator Taxa Associated with Benthic Organic Enrichment Using Different Video Camera Orientations
Bibliographic record
Abstract
Sutherland, T.F.; Sterling, A.M.; Shaw, K.L.; Blasco, N.N.J., and Bradford, M.J., 2019. Detecting indicator taxa associated with benthic organic enrichment using different video camera orientations. Journal of Coastal Research, 35(2), 467–479. Coconut Creek (Florida), ISSN 0749-0208.Two video cameras mounted on a remotely operated vehicle (ROV) were used to generate paired forward-facing (FF) and downward-facing (DF) observations of benthic epifauna along 10 single transects at eight marine finfish aquaculture sites in British Columbia, Canada. The abundance of mat-forming primary indicators of organic enrichment, such as sulphide-oxidizing bacteria and opportunistic polychaete complexes (OPC), were quantified through percentage coverage estimates. Coverage estimates for sulphide-oxidizing bacteria were strongly correlated between the FF and DF orientations across all substrate types. The occurrence of OPC was limited to a single mixed-substrate site, which provided the strongest FF vs. DF relationship within this study. In contrast to sulphide-oxidizing bacteria, epifaunal abundance (count data) revealed strong relationships between camera orientations for fine sediments and mixed sediments and a weaker relationship observed for vertical rock wall environments. Similar observations occurred for estimates of both sessile (dominated by plumose anemones) and motile taxa guilds comprising the total epifaunal community. Weaker relationships associated with the rock wall substrate are likely due to alternating blackout periods experienced by each camera orientation as the ROV passes vertical or ledge habitat zones. Overall, a combination of FF and DF video orientations may provide more robust abundance estimates for settings that are characterized by various substrate grades and structural and/or mat-forming taxa.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".