Invasive exotic plant monitoring at Curecanti National Recreation Area: 2023 field season
Bibliographic record
Abstract
Invasive exotic plant (IEP) species are one of the biggest threats to natural ecosystem integrity and biodiversity, and their control is a high priority for the National Park Service. The Northern Colorado Plateau Network (NCPN) selected early detection of IEPs as one of the 11 monitoring protocols implemented as part of its long-term monitoring program. This report represents work completed during the 2023 field season at Curecanti National Recreation Area (NRA). From June 21 to 27, 2023, we recorded 18 different priority IEP species during monitoring. We recorded 1,450 priority IEP patches along 55.9 km (34.7 miles) of four monitoring routes. Canada thistle (Breea arvensis), musk thistle (Carduus nutans), woolly mullein (Verbascum thapsus), and Russian thistle (Salsola spp.) were the most widespread species. Density of invasive plants was higher along the reservoir routes than the trail routes. Along the Blue Mesa Reservoir routes, percent cover of all invasive species combined was 1.41%. The Blue Mesa Reservoir 1 and Blue Mesa Reservoir 6 routes had much higher infestations per kilometer and higher overall percent cover in 2023 than compared to 2014. Large increases were observed in Canada thistle, musk thistle, Russian thistle, and woolly mullein. The number of infestations along the Dillon Pinnacles and Pine Creek trails declined from previous sampling periods.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".