Engaging with novel ecosystems
Bibliographic record
Abstract
N ovel ecosystems are assemblages of species that have not co-occurred historically; such ecosystems result directly and indirectly from human activities, are relatively stable, and occupy space alongside existing semi-natural or natural ecosystems in the world's landscapes and seascapes. Although recognized for at least three decades, novel ecosystems have heretofore been overlooked and apparently undervalued by both the scientific and conservation communities. As a consequence, they have also been largely ignored in the policy context. Novel ecosystems currently account for around 40% of the ice-free land on Earth, and probably a similar figure in the marine environment, although less work has been undertaken in the world's coastal seas and oceans in this regard. Such ecosystems are a blind spot in global conservation and restoration priorities as well as in discussions of environmental management and sustainable development. This oversight limits our effectiveness in intervening appropriately in ecosystems that are undergoing rapid environmental changes.
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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.020 |
| Scholarly communication | 0.017 | 0.023 |
| Open science | 0.003 | 0.028 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.040 | 0.014 |
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".