Canadian Airborne Biodiversity Observatory's Forest Inventory Field Survey Protocol v2
Bibliographic record
Abstract
Here, we describe the standardized protocol used by the Canadian Airborne Biodiversity Observatory (CABO) to conduct the field-based surveys of canopy trees at the forested study sites, Parc national du Mont Mégantic and Parc national du Mont Saint Bruno, located in southern Québec, Canada. These field-based surveys were conducted to relate field-based tree biodiversity data with aerial hyperspectral imagery data. Forest inventory plots (~706 m2) were systematically distributed to span the range of conditions present within the imaged areas. Plot dimensions were corrected to account for slope in the field and therefore, plots were circular (15 m radii) when viewed-from-above. Within each plot, we quantified the tree community defined as all individuals whose crowns extended into the general level of the canopy and those whose crowns were below the canopy but had a diameter at breast height (DBH) greater than 9 cm. Individuals were identified to species, positioned in relation to the plot center, and a suite of dendrometric properties (e.g., DBH, height) were quantified. To relate the field surveys with the hyperspectral imaging data, we took high-precision positions of plot centers. All data were collected using Fulcrum, a data collection application.
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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.116 | 0.034 |
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".