Classification and ecology of the mid‐seral Picea mariana forests of British Columbia
Bibliographic record
Abstract
Abstract. We sampled vegetation and soils of, and classified mid‐seral, even‐aged, fire‐origin, upland Picea mariana ecosystems in the Boreal White & Black Spruce and Sub‐boreal Spruce zones of British Columbia, Canada. We applied multi‐variate and tabular methods to analyse and synthesize the data from 121 plots according to the methods of biogeoclimatic ecosystem classification. We delineated seven basic vegetation units and described their vegetation and environmental features. However, the delineated units could not be related to neither of the taxonomies proposed for the North American boreal forest communities. Although species‐poor, the under‐storey vegetation in the sampled ecosystems provided for a sufficient floristic differentiation, which matched well the major edaphic differences between the units. The classification of mid‐seral boreal ecosystems may be more useful that based on old‐growth stands that are infrequent or lacking in the landscape due to wildfires.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".