Baffin Arctic Transect Vegetation Plots 2018-2023
Bibliographic record
Abstract
The 10 study sites for this project were along a 2000-kilometer (km) climate transect, from latitudes 58 degrees North (°N) to 72 °N, from northern Baffin Island to Nunavik. 289 plots were subjectively chosen to best represent the full range of vegetation types found in the vicinity of the sampled lakes. The plots characterized the immediate watershed around the lake, that provides input to the lake sediment. While this limited the area sampled, it produced a very consistent data set, with most of the remaining variation due to the climate and glacial history of the sites. The one exception was the GEN site, which was not located near a cored lake. Plots at this site reached from Generator Lake to the top of the nearby ridge (160 meter [m] elevation range compared to 5-30 m range at the other sites). The Braun-Blanquet method was used to describe the vegetation of the plots (relevés, Braun-Blanquet 1928). Plots were 1x1 square meter (m2). All taxa of vascular plants, bryophytes and lichens were recorded, and their percent cover within the plot was estimated. Taxa were identified to species in the field where possible, and sampled and identified later if necessary. Voucher specimens were deposited with the National Herbarium of Canada. Nomenclature followed Esslinger (2021) for lichens, Leclerc (2014) for bryophytes, and the PanArctic Flora for vascular plants (Walker et al. 2016). Environmental data describing the plots, including elevation, slope, aspect, soil characteristics and other variables were recorded and the plots were photographed. WARNING - Some cryptogam species identifications are still being finalized. Contact author for latest datasets.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.025 | 0.007 |
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".