Botanical Beach - Juan de Fuca Provincial Park - Drone Mapping
Bibliographic record
Abstract
This record contains an Orthomosaic and Digital Surface Model (DSM) of Botanical Beach, British Columbia, Canada, created from drone imagery. The intertidal area of Botanical Beach was mapped at low tide on July 22, 2020 by Will McInnes of the Hakai Institute. This survey was done to continue efforts by Hakai and its collaborators to map the intertidal habitats found within Botanical Beach. The images collected with the Phantom 4 Pro drone were stitched together in Pix4D Mapper to create an orthomosaic and digital surface model (DSM). A GNSS survey (Global Navigation Satellite System) was also conducted to collect ground control points for the drone survey. The survey and control point data allow the map information collected by the drone to be positioned accurately. Additional details are available in the project report. Datasets: -Orthomosaic (GeoTiff) -Digital surface model (GeoTiff) -3D site model (.obj or .las) -PDF maps of site
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.048 | 0.039 |
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".