Camera Surveys of the Subtidal Flora of Nova Scotia and Southwest New Brunswick 2022-2023
Bibliographic record
Abstract
To assess the current distribution of kelp beds and other macroalgae in Nova Scotia and Southwest New Brunswick, subtidal drop camera surveys were performed from 2022-2023 at 140 sites. For each site, a GoPro HERO 10 camera was towed along a deep (7-12m) and shallow (3-5m) depth contour until 20 images were acquired per depth. Where possible, species were identified from photos, with particular care given to kelps (defined here as orders Laminariales and Tilopteridales) and fucoids (order Fucales). Crust-forming algae was not counted. Percent cover was calculated using a 10x10 point grid overlaid on each image and recording the dominant cover type at each point. The depth (in meters) of each photo after correcting for tide height ranged from ~0.5m to ~12m. Depths were corrected to chart datum (lowest astronomical tide) using tide predictions from the nearest tide station, taken from tides.gc.ca. Sampling was performed between July and October.
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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 | 0.003 | 0.006 |
| 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) | 0.008 | 0.005 |
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".