Canopy Trees Survey Protocol - Forests of Southern Québec v1
Bibliographic record
Abstract
Here, we describe the standardized protocol used by the Canadian Airborne Biodiversity Observatory (CABO) to conduct ground-based surveys of canopy trees at forested sites: Parc national du Mont-Mégantic and Mont-Saint-Bruno, Québec. Ground-based canopy tree surveys were conducted in circular sample plots of 15 m radius, with plots distributed across gradients of interest (e.g., species composition, elevation, slope orientation, and logging history), and recorded in the Plots app in Fulcrum. For each sample plot, precise GPS coordinates of plot centres were taken, as well as slope angle and aspect. Within each sample plot, all trees that met the selection criteria were identified to species and geolocated relative to the plot center using the Postex system (Haglöf Sweden AB, Långsele, SE). In addition, height, diameter at breast height (DBH), canopy area, and crown dominance class were estimated for all selected trees. All data were entered into the Vegetation Surveys: Large Trees app in Fulcrum. In Parc national du Mont-Mégantic, for any tree species that had fewer than 10 individuals assigned as 'Dominant' or 'Co-dominant' (crown dominance classes), across all sample plots, additional individuals found outside sample plots were geolocated and measured to bring the sample size to 10 (data recorded in the Plants app in Fulcrum). The ground-based canopy tree surveys were conducted in order to be paired with remotely-sensed aerial hyperspectral imagery.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.115 | 0.017 |
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".