Rapid Response Plan for Management and Control of the Chinese Mitten Crab, Northeast United States and Atlantic Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Rapid Response Plan for Management and Control of the Chinese Mitten Crab is intended to guide efforts to mitigate the further introduction and spread of the Chinese mitten crab in the northeastern United States and Canada. Due to the unique challenges of invasive species introductions to marine and coastal ecosystems, the mitten crab and other existing and potential marine invasive species are more difficult and often more costly to manage or control than freshwater aquatic or terrestrial invasive species. These challenges include ecosystem connectivity across vast geographic areas, ocean currents and tidal influence, and shipping- and ballast-related vectors for larvae. Warming ocean and coastal waters and species range expansions influenced by climate change will further compound these issues. Recent and historical efforts to control or eradicate invasive mitten crab populations in other countries and in other parts of the United States have not been effective. More than a century of efforts to control or eradicate other marine invasive species, such as the European green crab, has also proven unsuccessful. For these reasons, it is prudent to focus available funds and regional capacity for early detection and rapid response planning on prevention, as we must assume that eradication is not likely should Chinese mitten crabs enter Rhode Island, Massachusetts, New Hampshire, Maine or Maritime Canada. The Sea Grant Programs in Massachusetts, New Hampshire and Maine worked with local, state, regional and federal stakeholders to establish a foundation for prevention, early detection and rapid response efforts of the Chinese mitten crab.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it