Rocky Intertidal RPAS Mapping - 2018 - 2020 - BC Central Coast - Canada
Bibliographic record
Abstract
The rocky intertidal dataset consists of drone imagery and associated data, collected as part of nearshore surveying at the Hakai Institute. The goals of this project are to: 1. Collect drone imagery associated with Nearshore survey sites, including affiliate research projects Relate RPAS-derived metrics to in situ field surveys 2. Derive metrics for nearshore habitat productivity and biodiversity using remotely sensed imagery This project has two levels, the first being a one-time inventory, and the second being a seasonal component. Level 1: one-time (i.e. non-seasonal) 3D models of all the sites for Nearshore Rocky intertidal, Pyropia, and Harley, Gehman, and Martone sites. Level 2: At least once per year, collect fine-resolution orthomosaics to classify barnacles, mussels, phyllospadix, fucus, and other primary cover types. We performed the Level 1 and Level 2 mapping at the following Hakai Rocky Intertidal sites as well as the level 1 and level 2 mapping at the three seasonal sites, we mapped sites requested by Alyssa Gehman / Chris Harley, Patrick Martone, and the seasonal Pyropia sites.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.022 |
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".