Is the spread of non-native plants in Alaska accelerating?
Bibliographic record
Abstract
Alaska has remained relatively unaffected by non-native plants; however, recently the state has started to experience an influx of invasive non-native plants that the rest of the U.S. underwent 60–100 years ago. With the increase in population, gardening, development, and commerce there have been more frequent introductions to Alaska. Many of these species, such as meadow hawkweed (Hieracium caespitosum), Canada thistle (Cirsium arvense), and spotted knapweed (Centaurea biebersteinii), have only localized populations in Alaska. Other species such as reed canary grass (Phalaris arundinacea) and white sweetclover (Melilotus officinalis), both formerly used in roadside seed mixes, are now very widespread and are moving into riparian areas and wetlands. We review the available literature and Alaska’s statewide invasive plant database (AKEPIC, Alaska Exotic Plant Clearinghouse) to summarize changes in Alaska’s non-native flora over the last 65 years. We suggest that Alaska is not immune to invasion, but rather that the exponential increase in non-native plants experienced elsewhere is delayed by a half century. This review highlights the need for more intensive detection and rapid response work if Alaska is going to remain free of many of the invasive species problems that plague the contiguous U.S.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".