Bibliographic record
Abstract
Approximately 30% of the world’s boreal forests and 10% of all forests worldwide are found in Canada, which has 43% of its area covered by forests. Canada is divided into eight woodland zones in addition to tundra and grasslands. Earthworm diversity, function, and a description will be provided for each forest area. A summary table will list the earthworm species with ecological type, forest regions, dominant tree species, and soil type in both the Canadian and American classification systems. A second table will illustrate the earthworm species with just the forest regions. Provided are a soil order map of Canada and a table indicating the different earthworm species prevalent in different forest soils. The appendix describes and pictures soil type profiles where earthworms have been recorded. Migration of arctic earthworms and climate change are topics of discussion. RÉSUMÉ Les forêts canadiennes couvrent 43% de sa masse continentale, ce qui représente 10% des forêts mondiales et 30% des forêts boréales mondiales. Il y a huit régions forestières au Canada, plus les prairies et la toundra. Chaque région forestière contiendra une description, une carte, la diversité et la fonction des vers de terre. Un tableau récapitulatif listera les espèces de vers de terre avec le type écologique, les régions forestières, les espèces d’arbres dominantes, le type de sol dans les systèmes de classification canadien et américain. Un deuxième tableau illustrera les espèces de vers de terre avec seulement les régions forestières. Une carte des ordres pédologiques au Canada et un tableau illustrant les espèces de vers de terre dans divers sols forestiers. L’annexe décrit et illustre les profils de type de sol où les vers de terre ont été enregistrés. La discussion inclut la migration des vers de terre arctiques et le changement climatique.
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 | 0.005 | 0.009 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".